Stem C ells O A
®
riginal rticle
Gene Expression Profile of Megakaryocytes from Human Cord Blood CD34+ Cells Ex Vivo Expanded by Thrombopoietin JEONG-AH KIM,a YU-JIN JUNG,b JU-YOUNG SEOH,b SO-YOUN WOO,b JEONG-SUN SEO,c HYUNG-LAE KIMa a
Departments of Biochemistry and bMicrobiology, College of Medicine, Ewha Womans University, Seoul, Korea; cCollege of Medicine, Seoul National University, Seoul, Korea and Macrogen Inc., Seoul, Korea Key Words. SAGE · Megakaryocytes · Cord blood · Thrombopoietin · ex vivo expansion · Microarray
A BSTRACT Previously, we investigated the process of megakaryocytopoiesis during ex vivo expansion of human cord blood (CB) CD34+ cells using thrombopoietin (TPO) and found that megakaryocytopoiesis was closely associated with apoptosis. To understand megakaryocytopoiesis at the molecular level, we performed a microserial analysis of gene expression (microSAGE) in megakaryocytes (MKs) and nonmegakaryocytes (non-MKs) derived from human CB CD34+ cells by ex vivo expansion using TPO, and a total of 38,909 tags, representing 8,976 unique
genes, were identified. In MKs, many of the known genes, including coagulation factor VII, P-selectin (CD62P), pim1, azurocidin, defensin, and CD48 were highly expressed; meanwhile, those genes encoding some small G proteins of the Ras family (Rab 7 and Rab 11A) and glutathione S transferase family (1, 4, A2, omega, and pi) showed lower expression levels in MKs. These gene expression profiles will be useful to understand megakaryocytopoiesis at the molecular level, including apoptosis and related signal transduction pathways. Stem Cells 2002;20:402-416
INTRODUCTION While thrombocytopenia remains a serious problem for patients receiving high-dose chemotherapy and hematopoietic stem cell (HSC) transplantation, the processes of differentiation and platelet formation from megakaryocytes (MKs) still remain to be elucidated [1]. The major limiting factor in investigating the process of megakaryocytopoiesis is the low frequency of MKs in hematopoietic tissues [2]. However, in vitro culture methods, along with the introduction of thrombopoietin (TPO) as an MK growth and developmental factor, provide a sufficient number of MKs, which can be used for biological as well as for structural analyses [3]. Previously, we investigated the process of
megakaryocytopoiesis during ex vivo expansion of human cord blood (CB) CD34+ cells using TPO and found that megakaryocytopoiesis was closely associated with apoptosis [4, 5]. However, the genes involved in the regulation of megakaryocytopoiesis have not yet been characterized. Serial analysis of gene expression (SAGE), described by Velculescu et al. [6], is based on the principle that a nucleotide sequence of 9-10 bases (a gene tag) corresponds to a unique transcript. The tag frequency directly reflects the abundance of the mRNA. It allows for the establishment of both a representative and a comprehensive different gene expression profile in various cell types and organs under physiological and pathological states. Since each template
Correspondence: Hyung-Lae Kim, M.D., Ph.D., Department of Biochemistry, College of Medicine, Ewha Womans University, Mok-6-dong 911-1, Yangchun-Ku, Seoul, 158-710, Korea. Telephone: 822-650-5727; Fax: 822-653-8891; email:
[email protected] Received March 14, 2002; accepted for publication June 19, 2002. ©AlphaMed Press 10665099/2002/$5.00/0
STEM CELLS 2002;20:402-416
www.StemCells.com
403
contains identifiable tags corresponding to many genes, this method allows us to have global gene expression profiles that are unknown. In the present study, we performed SAGE to analyze the gene expression profiles of MKs (CD61+ cells) derived from human CB CD34+ cells and compared them with those of non-MKs (CD61– cells). High-density oligonucleotide microarray hybridization and reverse transcription-polymerase chain reaction (RT-PCR) were used to validate the SAGE results. The data presented herein showed that many of the genes differentially expressed in MKs and non-MKs were involved in encoding proteins related to apoptosis and intracellular signaling pathways.
SAGE Analysis of Expanded Megakaryocytes cytometry with a different antibody reacting with MKs (FITC-conjugated anti-human CD61; BD). RNA Preparation Total RNA was prepared from the separated MK and non-MK fractions using the TRIZOL (GIBCO BRL; Grand Island, NY; http://www.lifetech.com) according to the manufacturer’s instructions. In order to remove DNA completely, the RNA samples were incubated with RNase-free DNase I (Takara Shoji; Tokyo, Japan; http://www.takara.co.jp). The quality of the RNA prepared was confirmed by analyzing the samples by electrophoresis on a 1.2% agarose/formaldehyde gel in MOPS (3-Morpholino propanesufonic acid) buffer. RNA samples were stored at -80°C until future use.
MATERIALS AND METHODS Purification of CB CD34+ Cells Human umbilical CB was obtained from full-term deliveries with informed consent. Mononuclear cells were isolated from CB using Ficoll-Hypaque (density 1.077; Pharmacia Biotech; Upsalla, Sweden; http://www.pnu.com) density centrifugation. After two cycles of plastic adherence for 60 minutes, the cells were washed and suspended in phosphatebuffered saline ([PBS] pH 7.4) containing 0.1% bovine serum albumin (BSA). The CD34+ cell fraction was positively isolated using an anti-CD34 monoclonal antibody (QBEND 10; Miltenyi Biotech; Bergisch Gladbach, Germany; http://www.miltenyibiotec.com) and CD34 progenitor cell isolation kit (Miltenyi Biotech), followed twice by the MiniMACS system (Miltenyi Biotech). The purity of the selected population was verified by flow cytometry with an anti-human CD34+ antibody conjugated with fluorescein isothiocyanate ([FITC] HPCA-2; Becton Dickinson [BD], Mountain View, CA; http://bdbiosciences.com). Purity was consistently more than 95%. Ex Vivo Expansion and Separation of MK and Non-MK Fractions The CD34+ cells were cultured at a density of 1.0 × 105 cells/ml in serum-free essential media supplemented with BSA, insulin, and transferrin (StemCell Technologies; Vancouver, BC, Canada; http://www.stemcell.com). Cultures were stimulated with recombinant human TPO (50 ng/ml; Kirin Brewery; Maebashi, Japan) alone. After 10 days, the MK fraction was separated from the non-MK fraction using an anti-CD41 (glycoprotein IIb/IIIa [GPIIb/IIIa]) monoclonal antibody (Dako; Copenhagen, Denmark; http://www.dako.dk) and a microbead-conjugated goat anti-mouse IgG (Miltenyi Biotech) followed twice by the MiniMACS system (Miltenyi Biotech). The purity of each separated fraction was verified by flow
SAGE Protocol SAGE was performed according to the Micro Serial Analysis of Gene Expression Detailed Protocol, version 1.0. Biotinylated oligo-dT-primer-annealed total RNA, 10 µg, was converted to cDNA with a BRL cDNA synthesis kit (GIBCO BRL) in a streptavidine-coated PCR tube (Roche; Mannheim, Germany; http://biochem.boehringermannheim.com). The cDNA was cleaved at Nla III, and was ligated to the oligonucleotide-containing recognition sites for BsmF I. After ligation, the bound cDNA was released from the matrix by digestion with BsmF I. SAGE tag overhangs were filled with Klenow, and tags from two pools were combined and ligated to each other. The ligation product was amplified by PCR, concatemerized, and cloned into the SphI site of pZero-1 (Invitrogen; Carlsbad, CA; http://www.invitrogen.com). Clones were sequenced with the BigDye terminator kit and analyzed using ABI 3700 automated sequencer (Perkin-Elmer; Branchberg, CT; http://www.perkinelmer.com). Sequence files were analyzed by means of SAGE analysis software, version 4.12. Statistical analysis of the data (Monte Carlo test) was performed using SAGE software, version 4.12 (courtesy of Victor Velculescu and Ken Kinzler, Johns Hopkins University School of Medicine; Baltimore, MD) [6]. The identities of the mRNAs corresponding to the SAGE tags were determined through inspection and comparison with the SAGEmap (www.ncbi.nlm.nih.gov/SAGE/SAGEtag.cgi) and UniGene (www.ncbi.nlm.nih.gov/UniGene) databases. Microarray Protocol Total RNA (5 µg) was converted into double-stranded cDNA using the cDNA synthesis system (Roche) with T7(dT)24 primer. Then, each cDNA was purified using the RNeasy kit (Qiagen; Valencia, CA; http://www.qiagen.com). Each Cy3- (MK), or Cy5- (non-MK) labeled cRNA was synthesized using the Megascript T7 kit (Ambion; Austin, TX;
Kim, Jung, Seoh et al.
404
http://www.ambion.com), with Cy3-CTP and Cy5-CTP (APB; Uppsala, Sweden; http://www.apbiotech.com). The cRNA was purified using RNeasy (Qiagen). Fifteen micrograms of each purified cRNA were mixed and fragmented in fragmentation buffer (40 mM Tris [pH 8.1], 100 mM KOAc, and 30 mM MgOAC) by heating to 94°C for 15 minutes. Fragmented cRNA was mixed with hybridization buffer, containing 100 mM MES, 1 M NaCl, 20 mM EDTA, and 0.01% Tween 20, and hybridized with MAGIC II-10 K Oligo Chip (Macrogen; Seoul, Korea; http://www.macrogen.com) for 16 hours at 42°C. All preparations met Macrogen’s recommended criteria for use on their expression arrays. Arrays were then washed and scanned with an array scanner (APB). Acquired images were processed and analyzed statistically for interpretation of spot intensity results using Imagene version 4.1 software (Roche). Nonbiological factors that might contribute to the
variability of data were minimized using global normalization/scaling with data from all probe sets. Each chip contains a total of 10,368 elements, of which 10,108 are unique genes/clusters. The length of oligonucleotides was 50-mer. Subsets of genes were selected based on differential Cy3/Cy5 expression ratios that were ≥|2| in response. RT-PCR One microgram of total RNA from each sample was used as a template for the RT reaction. The total RNA was reverse transcribed in 20 µl of 10 mM Tris-HCl (pH 8.3), 6.5 mM MgCl2, 50 mM KCl, 10 mM dithiothreitol (DTT), 1 mM of each dNTP, 0.5 µg oligo dT primer, and 50 U of Superscriptase II (GIBCO BRL) for 1 hour at 42°C. The conditions of PCR were as follows, in a 25 µl reaction, 0.4 µM of each primer (Table 1), 125 µM of each dNTP mixture, 50 mM KCl, 10 mM Tris-HCl (pH 8.3), and 1.5 mM
Table 1. Transcript profiles in human CD34+-derived megakaryocytes Abundance (%) 4.48 1.02
Tag sequence CCCAACGCGC TGTGTTGAGA
0.70 0.62 0.59 0.58 0.58 0.55 0.54 0.53 0.53 0.53 0.52 0.51 0.50 0.50 0.50 0.50 0.48 0.47 0.47 0.47
CTTCTTGCCC GGCTGGGGGC GCCGAGGAAG CACAAACGGT TGGTGTTGAG AGGCTACGGA CCCTGGGTTC GCAGCCATCC CCCGTCCGGA GGATTTGGCC GCATAATAGG CCCCAGCCAG GCTGTTCATT TGGCCCCAGG CTCAACATCT TTGGTCCTCT CGCCGGAACA GCCGTGTCCG CTGGCCTCCC ATGCAGAGCT
0.46 0.46 0.46 0.46 0.46
TCACCCACAC ATTCAGAGCT AAGACAGTGG ATCAAGGGTG TTGGTGAAGG
Description (UniGene cluster) Hs.272572: hemoglobin, alpha 2, Hs.334804: hemoglobin, alpha 1 Hs.181165: eukaryotic translation elongation factor 1 alpha 1, Hs.274466: eukaryotic translation elongation factor 1 alpha 1-like 14 Hs.272572: hemoglobin, alpha 2, Hs.334804: hemoglobin, alpha 1 Hs.75721: profilin 1 Hs.285405: ribosomal protein S12, Hs.288224: hypothetical protein Hs.195453: ribosomal protein S27 (metallopanstimulin 1) Hs.275865: ribosomal protein S18 Hs.119122: ribosomal protein L13a Hs.111334: ferritin, light polypeptide Hs.4437: ribosomal protein L28 Hs.180842: ribosomal protein L13 Hs.119500: ribosomal protein, large P2 Hs.184108: ribosomal protein L21 Hs.252259: ribosomal protein S3, Hs.334861: hypothetical protein FLJ23059 Hs.288986: survival of motor neuron 1, telomeric Hs.268571: apolipoprotein C-I Hs.73742: ribosomal protein, large P0 Hs.108124: ribosomal protein S4, X-linked, Hs.324406: ribosomal protein L41 Hs.286: ribosomal protein L4, Hs.334822: hypothetical protein MGC4485 Hs.241507: ribosomal protein S6 Hs.73849: apolipoprotein C-III Hs.283108: hemoglobin, gamma G, Hs.298161: myosin, light polypeptide 4, alkali;atrial, embryonic Hs.322680: Homo sapiens cDNA: FLJ21547 fis, clone COL06206 Hs.305960: hemoglobin, gamma A Hs.5566: ribosomal protein L37a Hs.157850: ribosomal protein L9 Hs.288031: sterol-C5-desaturase (fungal ERG3, delta-5-desaturase)-like, Hs.75968: thymosin, beta 4, X chromosome
SAGE Analysis of Expanded Megakaryocytes
405
Table 1. Transcript profiles in human CD34+-derived megakaryocytes (continued) Abundance (%)
Tag sequence
Description (UniGene cluster)
0.46
TGGACGCGCT
Hs.93194: apolipoprotein A-I
0.46
GGGCTGGGGT
Hs.183698: ribosomal protein L29, Hs.90436: sperm-associated antigen 7
0.45
CTCCTCACCT
Hs.119122: ribosomal protein L13a, Hs.93213: BCL2-antagonist/killer 1
0.45
CGCCGCCGGC
Hs.182825: ribosomal protein L35
0.45
CTGTTGGTGA
Hs.3463: ribosomal protein S23
0.45
AAGGTGGAGG
Hs.163593: ribosomal protein L18a
0.44
GAGGGAGTTT
Hs.76064: ribosomal protein L27a
0.44
GTGGGTTGGC
Hs.195432: aldehyde dehydrogenase 2 family (mitochondrial)
0.44
TCCTGCCCCA
Hs.171814: parathymosin
0.19
GAGCCCAGCC
Hs.72885: azurocidin 1 (cationic antimicrobial protein 37)
0.19
GGCAAGCCCC
Hs.187577: SRY (sex-determining region Y)-box 21, Hs.252574: ribosomal protein L10a
0.19
TCCTTAGGCT
Hs.274309: erythroid differentiation-related factor
0.18
CCCATCCGAA
Hs.91379: ribosomal protein L26
0.18
GGGGAAATCG
Hs.76293: thymosin, beta 10
0.18
GGAAAAGTGG
Hs.297681: serine (or cysteine) proteinase inhibitor, clade A, member 1
0.18
CGACCCCACG
Hs.169401: apolipoprotein E
0.17
TGTGCTGAAC
Hs.284176: transferrin
0.17
GACGTGTGGG
Hs.119192: H2A histone family, member Z
0.17
GAAAAGGGTT
Hs.296398: Homo sapiens mRNA; cDNA DKFZp586E1124
0.17
TGGATCCTGA
Hs.117848: hemoglobin, epsilon 1, Hs.283108: hemoglobin, gamma G, Hs.305960: hemoglobin, gamma A
0.17
GCCTGTATGA
Hs.180450: ribosomal protein S24
0.15
GAGTCAGGAG
Hs.181271: CGI-120 protein
0.15
GTACTGTGGC
Hs.74276: chloride intracellular channel 1
MgCl2 AmpliTaq (Perkin-Elmer) were used. The PCR protocol consisted of denaturing for 30 seconds at 94°C, annealing for 30 seconds at 55°C, and elongating for 1 minute at 72°C. Amplification was performed for 25 to 30 cycles. Primers used were as follows. Apoptotic protease activating factor-1 (APAF-1): sense 5′-CTT GGA TGA TGT TTG GGA CTC TTG-3′, antisense 5′-GAA ACG ACT TTC CAT TCC GAT CAC-3′; CD 48: sense 5′-CCA GAA CAG TGT GCT TGA AAC CAC-3′, antisense 5′-TGG TCA GCC TAT ACA GTC TCT GTC C-3′; defensin: sense 5′-TTG CTG CCA TTC TCC TGG TG -3′, antisense 5′-GAG GAA AGG AAA TTG AGC AGA AGG-3′; pim-1: sense 5′-CGG ATT CTA ACC TGG AGG TCA-3′, antisense 5′-CTC AGA TAA AAC CAG CAG GCT ACC-3′; P-selectin: sense 5′-AAC ACA AGC CAC AGA AGC CAG G-3′, antisense 5′-TGG GTC ATT TGA GGG ACA GTG AC-3′; KIAA0614: sense 5′-CTT GAA TGG ACT TGT CAG CTA CCT C-3′, antisense 5′-TGC CAG CCT TTG AAC TTG CTC-3′; β-actin: sense 5′-AAG AGG ACC CAG ATC ATG TTT GAG-3′, antisense 5′-AGG AGG AGC AAT GAT CTT GAT CTT-3′.
RESULTS SAGE Tag Abundance in MK and Non-MK Fractions To reduce individual variation in gene expression, we obtained CB from four volunteers. The purified CB CD34+ cells were cultured in a serum-free liquid culture system stimulated with TPO for 10 days. Under these conditions, the cells differentiated into CD41+ (GPIIb) cells with characteristic MK morphology [5]. The total RNA prepared from these MK and non-MK fractions was processed with SAGE analysis. A total of 38,909 tags, including 20,580 and 18,329 tags from MK and non-MK fractions, respectively, allowed 8,976 different transcripts. The expressed genes were searched for in the UniGene database to identify individual genes. The top 50 transcripts in the two fractions are listed in Tables 1 and 2. Gene tags that had no reliable matches in UniGene clusters were excluded from the list. The most abundantly expressed genes identified in both cell fractions included hemoglobin family genes, ferritin light chain, profilin 1, and genes from the apolipoprotein family,
Kim, Jung, Seoh et al.
406
Table 2. Transcript profiles in human CD34+-derived non-megakaryocytes Abundance (%)
Tag sequence
Description (UniGene cluster)
2.28
CCCAACGCGC
Hs.272572: hemoglobin, alpha 2, Hs.334804: hemoglobin, alpha 1
0.94
TGTGTTGAGA
Hs.181165: eukaryotic translation elongation factor 1 alpha 1, Hs.274466: eukaryotic translation elongation factor 1 alpha 1-like 14
0.86
CTTCTTGCCC
Hs.272572: hemoglobin, alpha 2, Hs.334804: hemoglobin, alpha 1
0.71
ATGCAGAGCT
Hs.283108: hemoglobin, gamma G, Hs.298161: myosin, light polypeptide 4, alkali;atrial, embryonic
0.59
CCCTGGGTTC
Hs.111334: ferritin, light polypeptide
0.55
CCCCAGCCAG
Hs.252259: ribosomal protein S3, Hs.334861: hypothetical protein FLJ23059
0.55
TTGGTCCTCT
Hs.108124: ribosomal protein S4, X-linked, Hs.324406: ribosomal protein L41
0.53
CACAAACGGT
Hs.195453: ribosomal protein S27 (metallopanstimulin 1)
0.53
TGGTGTTGAG
Hs.275865: ribosomal protein S18
0.51
TTGGTGAAGG
Hs.288031: sterol-C5-desaturase (fungal ERG3, delta-5-desaturase)-like, Hs.75968: thymosin, beta 4, X chromosome
0.49
CTGGCCTCCC
Hs.73849: apolipoprotein C-III
0.48
CTCAACATCT
Hs.73742: ribosomal protein, large P0
0.48
GGCTGGGGGC
Hs.75721: profilin 1
0.47
CCCGTCCGGA
Hs.180842: ribosomal protein L13
0.46
GCCGTGTCCG
Hs.241507: ribosomal protein S6
0.46
GGGCTGGGGT
Hs.183698: ribosomal protein L29, Hs.90436: sperm-associated antigen 7
0.45
ATCAAGGGTG
Hs.157850: ribosomal protein L9
0.45
AAGGTGGAGG
Hs.163593: ribosomal protein L18a
0.45
CGCCGGAACA
Hs.286: ribosomal protein L4, Hs.334822: hypothetical protein MGC4485
0.45
GCATAATAGG
Hs.184108: ribosomal protein L21
0.45
GCCTGTATGA
Hs.180450: ribosomal protein S24
0.44
GCCGAGGAAG
Hs.285405: ribosomal protein S12, Hs.288224: hypothetical protein
0.44
GGATTTGGCC
Hs.119500: ribosomal protein, large P2
0.44
GGCTGGGGCC
Hs.928: proteinase 3, Hs.99863: elastase 2, neutrophil
0.44
CCTAGCTGGA
Hs.182937: peptidylprolyl isomerase A (cyclophilin A), Hs.267690: KIAA1228 protein
0.44
AAGACAGTGG
Hs.5566: ribosomal protein L37a
0.44
CTGTTGGTGA
Hs.3463: ribosomal protein S23
0.44
ATGGCTGGTA
Hs.182426: ribosomal protein S2
0.43
TCCTGCCCCA
Hs.171814: parathymosin
0.43
CGACCCCACG
Hs.169401: apolipoprotein E
0.42
TGGACGCGCT
Hs.93194: apolipoprotein A-I
0.42
GTGGGTTGGC
Hs.195432: aldehyde dehydrogenase 2 family (mitochondrial)
0.19
AGGCTACGGA
Hs.119122: ribosomal protein L13a
0.19
GCAGCCATCC
Hs.4437: ribosomal protein L28
0.19
GTGAAGGCAG
Hs.155101: ATP synthase, H+ transporting, mitochondrial F1 complex, alpha subunit, isoform 1, cardiac muscle, Hs.77039: ribosomal protein S3A
0.18
TGGCCCCAGG
Hs.268571: apolipoprotein C-I
0.18
CGCCGCCGGC
Hs.182825: ribosomal protein L35
0.18
GAGGGAGTTT
Hs.76064: ribosomal protein L27a
0.17
GGAAAAGTGG
Hs.297681: serine (or cysteine) proteinase inhibitor, clade A, member 1
0.17
TGGATCCTGA
Hs.117848: hemoglobin, epsilon 1, Hs.283108: hemoglobin, gamma G, Hs.305960: hemoglobin, gamma A
0.17
CCGTCCAAGG
Hs.80617: ribosomal protein S16
0.17
AGCACCTCCA
Hs.75309: eukaryotic translation elongation factor 2
SAGE Analysis of Expanded Megakaryocytes
407
Table 2. Transcript profiles in human CD34+-derived non-megakaryocytes (continued) Abundance (%)
Tag sequence
Description (UniGene cluster)
0.16
CAGCCTTGGA
Hs.65648: RNA-binding motif protein 8A
0.15
ATTCAGAGCT
Hs.305960: hemoglobin, gamma A
0.15
TGACTGTGCT
Hs.26944: neurogranin (protein kinase C substrate, RC3)
0.15
AGGGCTTCCA
Hs.29797: ribosomal protein L10, Hs.334853: hypothetical protein FLJ23544
0.15
TCAGATCTTT
Hs.108124: ribosomal protein S4, X-linked
0.14
GGGGAAATCG
Hs.76293: thymosin, beta 10
0.14
CGCTGGTTCC
Hs.179943: ribosomal protein L11
0.14
GGCAACTGCC
Hs.39911: Homo sapiens mRNA for FLJ00089 protein, partial cds
followed by housekeeping ribosomal protein coding genes (Tables 1 and 2). Survival of motor neuron 1 (0.51%), azurocidine 1 (0.19%), and CGI 120 protein coding gene (0.15%) was highly expressed in the MK fraction. By contrast, the genes encoding eukaryotic translation elongation factor 2 (0.17%) and neurogranine (0.15%) were detected only in the non-MK fraction. Comparison of Expression Patterns Between MK and nonMK Fractions Expressed transcripts of MKs and non-MKs were compared (Fig. 1). Each dot in Figure 1 represents a gene expressed in these two fractions. Although the expression levels of most of the transcripts were similar in both fractions, significant differences in expression levels between the two fractions were found in many transcripts.
Figure 1. Comparison of gene expression between MKs and nonMKs. SAGE tag frequencies for MK and non-MK fractions are plotted on a logarithmic scale, using a total of 20,580 tags from MKs (x axis) and 18,329 tags from non-MKs (y axis). To avoid division by 0, we used a tag value of 1 for any tag that was not detectable in both samples, and the tag populations were normalized.
Tables 3 through 5 show the genes differentially expressed in MKs and non-MKs. Unidentified and multiple matched genes were excluded from the tables. Table 3 shows the top 50 transcripts that had greater expression levels in MKs, than in non-MKs. The most extreme of these was identified to be eukaryotic elongation factor 1 beta 1 (45-fold), followed by CGI-135 protein (38-fold), protein associated with PRK1 (38-fold), thioredoxin peroxidase (38-fold), and so on. The transcripts with greater expression levels in MKs could be classified into several groups according to the functional relevance: genes encoding gene-expression-related proteins, such as eukaryotic translation elongation factor, CAAT/enhancer binding protein, and cyclic AMP (cAMP) responsive element binding protein; splicing-related and RNA-binding proteins, such as RNase 6, small nuclear ribonucleoprotein D2, U2 small nuclear ribonucleoprotein auxiliary factor, RD (arginin and aspartate) RNA-binding protein, and splicing factor 3a; metabolic pathway-related proteins, such as cytochrome c synthase, cytochrome b-245, lactate dehydrogenase B, malate dehydrogenase 2, and NADH dehydrogenase 1 beta; heat shock proteins, such as Hsp 90 and Hsp 40 homologue; and surface marker proteins, such as CD48, and CD62P (P-selectin). The transcripts with lower expression levels in MKs (Table 4) were small G-protein-related proteins, such as ras guanyl-releasing protein 2, ral guanine nucleotide dissociation stimulator, rho/rac guanine nucleotide exchange factor 2, and rab 11A; surface marker proteins, such as CD37; proteasome subunits; and ATP synthases. Table 5 shows the differentially expressed genes grouped into several categories according to their functional relevance. Genes in the EST database or unidentified in the GenBank database were excluded from Table 5. While those genes related to the cytoskeletal system, such as tubulin and actin-binding proteins, showed almost equal or lower expression in MKs, the genes encoding transporter and channel proteins, such as arsenite transporter and transportin-SR, were expressed more in MKs. Most of the ribosomal proteins were
Kim, Jung, Seoh et al.
408
Table 3. Transcripts with greater expression levels in megakaryocytes Fold
Number MKs
SAGE tag
Description (UniGene cluster)
Non-MKs
45
45
0
GCATTTAAAT
Hs.261802: eukaryotic translation elongation factor 1 beta 1
38
38
0
TGCTTTGGGA
Hs.84344: CGI-135 protein
38
38
0
GGTTTGTGTG
Hs.83954: protein associated with PRK1
38
38
0
CTCTGTTGAT
Hs.83383: thioredoxin peroxidase (antioxidant enzyme)
38
38
0
GGACCTGCGC
Hs.8297: ribonuclease 6 precursor
38
38
0
GGGGTAAGAA
Hs.80423: prostatic-binding protein
38
38
0
CTGAGTCTCC
Hs.77269: G protein, alpha inhibiting activity polypeptide 2
38
38
0
CAGGTTGACA
Hs.69235: transportin-SR
38
38
0
GACACCAGGG
Hs.42853: cAMP responsive element-binding protein-like 1
38
38
0
GGCAATATGG
Hs.197289: rab3, noncatalytic subunit (150 kD)
35
35
0
GAAATGATGA
Hs.288856: prefoldin 5
35
35
0
CAGACCATTG
Hs.211612: SEC24 (S. cerevisiae)-related gene family, member A
31
31
0
GTGCTGGAGA
Hs.53125: small nuclear ribonucleoprotein D2 polypeptide
27
27
0
CAGGGCCTGA
Hs.7655: U2 small nuclear ribonucleoprotein auxiliary factor
23
23
0
CTTTTTTCCC
Hs.901: CD48 antigen (B-cell membrane protein)
23
23
0
ATTGGCTTAA
Hs.75323: prohibitin
23
23
0
CTGCAGAGTG
Hs.211571: holocytochrome c synthase (cytochrome c hemelyase)
23
23
0
GTGATGGTGT
Hs.197345: thyroid autoantigen 70 kD (Ku antigen)
23
23
0
AGCCCTGGCT
Hs.15896: kendrin
23
23
0
GCAAAACCAG
Hs.15071: chaperonin-containing TCP1, subunit 8 (theta)
23
23
0
CCTTCCAAAT
Hs.111076: malate dehydrogenase 2, NAD (mitochondrial)
23
23
0
GCCAGTGCCT
Hs.106061: RD RNA-binding protein
23
23
0
CAGCTTGCAA
Hs.105465: small nuclear ribonucleoprotein polypeptide F
21
21
0
GGCTCCCACT
Hs.74335: heat shock 90 kD protein 1, beta
19
38
2
CAGTCGGTCA
Hs.77579: apoptotic protease-activating factor
12.5
25
2
ACTCAGAAGA
Hs.198272: NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 2
11.6
35
3
TCTTCCAGGA
Hs.74267: ribosomal protein L15
8.2
33
4
GTGGCGAATG
Hs.36989: coagulation factor VII
8
24
3
ACCGCCGTGG
Hs.68877: cytochrome b-245, alpha polypeptide
8
8
0
AAAATGCAGA
Hs.80741: propionyl coenzyme A carboxylase, alpha polypeptide
7.6
23
3
AACTTGATGG
Hs.23170: homologue of yeast SPB1
6.7
401
59
GCTGTTCATT
Hs.288986: survival of motor neuron 1, telomeric
6.7
27
4
CTGAGTGAGT
Hs.177812: uncharacterized bone marrow protein BM046
6
30
5
GAGTTTGGCC
Hs.102402: Mad 4 homologue
5.2
21
4
TCCTAGCCTG
Hs.74711: DnaJ (Hsp40) homologue, subfamily C, member 8
5.2
21
4
GTGAACTAAT
Hs.5184: TH1 drosophila homologue
5.2
21
4
GATCACAGTT
Hs.234489: lactate dehydrogenase B
5
35
7
GGGTGTGTAT
Hs.83347: angio-associated, migratory cell protein
5
35
7
GTAGTATACA
Hs.81170: pim-1 oncogene
5
35
7
GAGACCCTGG
Hs.8088: similar to S. cerevisiae Sec6p and R. norvegicus rsec6
5
35
7
TCACCGTGGA
Hs.73800: P-selectin
5
35
7
CCTCAGCCCT
Hs.63489: protein tyrosine phosphatase, nonreceptor type 6
4.3
35
8
GGGGGTGAAG
Hs.76171: CCAAT/enhancer-binding protein (C/EBP), alpha
4.3
35
8
CAGCTGGGGC
Hs.172550: polypyrimidine tract-binding protein (heterogeneous nuclear ribonucleoprotein I)
SAGE Analysis of Expanded Megakaryocytes
409
Table 3. Transcripts with greater expression levels in megakaryocytes (continued) Fold
Number
SAGE tag
Description (UniGene cluster)
MKs
Non-MKs
3.9
55
14
ACATCATCGA
Hs.182979: ribosomal protein L12
3.3
27
8
GGCATCTGGC
Hs.7910: RING1 and YY1 binding protein
3.3
27
8
GCTCCACTGG
Hs.75709: mannose-6-phosphate receptor
3.3
27
8
CTGTGAGTTC
Hs.272100: SMS3 protein
3.3
27
8
CTCTACAGTG
Hs.24322: ATPase, H+ transporting, lysosomal (vacuolar proton pump) 9 kD
1.7
14
8
CTGGCAGATT
Hs.77897: splicing factor 3a, subunit 3, 60 kD
The 50 transcripts displaying the highest expression levels in MKs compared with non-MKs are listed. Number is the number of times the tag was identified. Each number of tags was normalized to 50,000.
Table 4. Transcripts with lower expression levels in megakaryocytes Fold
Number
SAGE tag
Description (UniGene cluster)
MKs
Non-MKs
44
0
44
GGGTGCTTGG
Hs.6551: ATPase, H+ transporting, lysosomal, subunit 1
44
0
44
CAGCTCCGCT
Hs.82113: dUTP pyrophosphatase
44
0
44
CAGCTGAGGG
Hs.99491: RAS guanyl-releasing protein 2
42
0
42
CCACTGCATT
Hs.199245: inactivation escape 1
37
0
37
CAAGACGGGG
Hs.106185: ral guanine nucleotide dissociation stimulator
37
0
37
CCACCGCACT
Hs.115325: RAB7, member RAS oncogene family-like 1
37
0
37
GACAATGCCA
Hs.155433: ATP synthase, H+ transporting, mitochondrial F1 complex, gamma polypeptide 1
37
0
37
CCTCCCTGAT
Hs.167013: dynamin 2
37
0
37
GAGCCTTGGT
Hs.183994: protein phosphatase 1, catalytic subunit, alpha
37
0
37
GCAGTGGCCT
Hs.184276: solute carrier family 9 (sodium/hydrogen exchanger), isoform 3 regulatory factor 1
37
0
37
ATGGTGTATG
Hs.239189: glutaminase
37
0
37
AGGGTGTTTT
Hs.75842: dual-specificity tyrosine phosphorylation-regulated kinase 1A
37
0
37
GAGCGGGATG
Hs.77060: proteasome subunit, beta type, 6
37
0
37
ACACTTCTTT
Hs.83381: guanine nucleotide-binding protein 11
28
0
28
GGGCATCTCT
Hs.76807: MHC class II, DR alpha
22
0
22
CAAGCAGGAC
Hs.179516: integral type I protein
22
0
22
CCCTAGGTTG
Hs.3989: plexin B2
22
0
22
CCACACCTCT
Hs.54673: tumor necrosis factor superfamily, member 13
22
0
22
AAATGCCACA
Hs.65450: reticulon 4
22
0
22
CCCCTGGCTG
Hs.920: modulator recognition factor I
14
0
14
ACCAAGGTGG
Hs.114231: C-type lectin-like receptor-2
14
0
14
ACATAGACCG
Hs.173594: serine (or cysteine) proteinase inhibitor (alpha-2 antiplasmin, pigment epithelium-derived factor), member 1
14
0
14
ACAGTGTGAG
Hs.173824: thymine-DNA glycosylase
12
0
12
AAGGAAGATC
Hs.11465: glutathione transferase omega
12
0
12
AAGTTTGCCT
Hs.28988: glutaredoxin (thioltransferase)
12
0
12
ACCTGAAACC
Hs.315417: rho/rac GEF 2
11
0
11
AATAAAGTTG
Hs.117176: poly(A)-binding protein, nuclear 1
8.0
0
8
ACGCTCTCGA
Hs.153053: CD37 antigen
Kim, Jung, Seoh et al.
410
Table 4. Transcripts with lower expression levels in megakaryocytes (continued) Fold
Number
SAGE tag
Description (UniGene cluster)
MKs
Non-MKs
8.0
0
8
AATGAGTTTG
Hs.283740: DC6 protein
8.0
0
8
AGAAGTGTCC
Hs.85226: lipase A, lysosomal acid, cholesterol esterase
6.7
7
47
TCACCGGTCA
Hs.290070: gelsolin (amyloidosis, Finnish type)
6.2
10
62
CGACGAGGAG
Hs.9999: epithelial membrane protein 3
6.0
6
36
CGCCGCGGTG
Hs.4835: eukaryotic translation initiation factor 3, subunit 8
4.4
10
44
GGAAGCACGG
Hs.148495: proteasome 26S subunit, non-ATPase, 4
4.4
10
44
GAGGTCCCTG
Hs.336907: proteasome subunit, alpha type, 6
4.4
10
44
CCCCCTCCGG
Hs.48375: small nuclear ribonucleoprotein polypeptide N
4.3
6
26
GGGCTGGGCC
Hs.100071: 6-phosphogluconolactonase
4.3
6
26
CCTCCACCTA
Hs.146354: peroxiredoxin 2
4.3
6
26
ACCTCAGGAA
Hs.177516: high-density-lipoprotein-binding protein (vigilin)
4.3
6
26
CCGTGCTCAT
Hs.9857: carbonyl reductase
4.3
10
43
CTTCCTCTGG
Hs.303023: beta tubulin 1, class VI
4.0
6
24
CAGGACGGGC
Hs.180616: CD36 (collagen type I receptor, thrombospondin receptor)-like 1
4.0
6
24
GCCACTGACC
Hs.7740: oxysterol-binding protein-like 1
4.0
2
8
AAACATTGGG
Hs.8203: endomembrane protein emp70 precursor isolog
3.9
10
39
GTCAGCCTGT
Hs.62643: dual adaptor of phosphotyrosine and 3-phosphoinositides
3.7
12
44
TTCCACCAAC
Hs.75618: RAB11A
3.4
12
41
GCACCTGTCG
Hs.1239: alanyl aminopeptidase
3.2
13
41
GGGCACCTGG
Hs.129826: tetraspan transmembrane 4 super family
2.0
23
46
TGAAGGAGCC
Hs.89399: ATP synthase, H+ transporting, mitochondrial F0 complex, subunit c (subunit 9), isoform 2
1.4
10
14
CTTTTGGCTG
Hs.48876: farnesyl-diphosphate farnesyltransferase 1
The 50 transcripts displaying the lowest expression levels in MKs compared with non-MKs are listed. Number is the number of times the tag was identified. Each number of tags was normalized to 50,000.
Table 5. Differential tag abundance in megakaryocytes (MKs) and non-megakaryocytes (non-MKs) Gene (Functional category)
UniGene Acc. No
Cytoskeleton, ion channel, and transporter
SAGE Tag sequence
Hs.
MKs
Microarray Non-MKs
2log(MKs/non-MKs)
No.
No.
Fold
Integrin alpha itga6
227730
CTGTAAGGAT
6
4
2.8
Talin (TLN)
278559
CTCCAATAAA
6
1
1.62
Membrane protein, palmitoylated 1 (55 kD) (MPP1)
1861
Plasma membrane calcium ATPase isoform atp2b1 alternative splice products alternatively spliced
TTTGGCACCA
6
4
1.4
GTGGCAGGCG
23
8
2.05
38
7
1.17
Tip associating protein tap; similar to yeast mRNA export factor mex67p
323502
GCGGACGAGG
H beta 58 homologue
266933
CAAAAAAATT
6
1
1.17
41735
AGGACATCCT
45
37
0.04
165439
AGGTGCGGGG
38
7
0.28
184108
CTGTTGGCAT
6
8
-1.05
Purinergic receptor P2X, ligand-gated ion channel ArsA (bacterial) arsenite transporter Ribosomal protein ribosomal protein L21 (RPL21)
SAGE Analysis of Expanded Megakaryocytes
411
Table 5. Differential tag abundance in megakaryocytes (MKs) and non-megakaryocytes (non-MKs) (continued) Gene (Functional category)
UniGene Acc. No
SAGE
Microarray
Tag sequence
MKs
Non-MKs
2log(MKs/non-MKs)
Ribosomal protein S13 (RPS13)
165590
GTGTTGCACA
54
68
-1.08
Ribosomal protein L23 (RPL23)
234518
ATTCTCCAGT
23
32
-1.09
Ribosomal protein S16 (RPS16)
80617
CCGTCCAAGG
74
89
-1.28
Ribosomal protein S11 (RPS11)
182740
TCTGTACACC
33
64
-1.31
Ribosomal protein S2 (RPS2)
182426
ATGGCTGGTA
74
219
-1.39
Ribosomal protein S24 (RPS24)
180450
GCCTGTATGA
82
223
-1.59
Ribosomal protein S23 (RPS23)
3463
CAAAAGGAAT
1
4
-1.59
137168
TGCCCTGAGC
6
1
1.29
Nuclear factor (erythroid-derived 2), 45 kD
75643
CGCCAACAGC
38
8
0.7
Nuclear factor (erythroid-derived 2)-like 2
155396
CTACGTGATG
38
6
-0.25
42853
GACACCAGGG
38
0
-0.19
Transcription regulation SMAD- and olf-interacting zinc finger protein oaz
CAMP responsive element binding protein-like 1 Rsec15-like protein
272374
CTTGTAATCC
1
4
-1.03
X-box binding protein 1 (XBP1)
149923
CAATTAAAAG
6
8
-1.06
Zinc finger protein 2
181696
GTTCACACGG
1
8
-1.09
Eukaryotic translation initiation factor 3, subunit 6 (48 kD) (EIF3S6)
106673
GTTTTAGGCA
1
4
-1.78
Tpt1 translationally controlled tumor protein tctp exons 1-6
279860
CTCATAGCAG
27
36
-1.2
247954
TACCTGATGA
6
1
1.57
Apoptosis and proteolysis Thrombospondin-1 Calpain 1, (mu/I) large subunit (CAPN1)
2575
GGCTCGGGAT
23
8
1.15
77579
CAGTCGGTCA
38
2
0.65
CCTGTGATCC
6
4
1.05
2161
ATCGCACCAC
6
22
-1.08
Arginyl aminopeptidase (aminopeptidase B) (RNPEP)
283667
GCCCCTGCCT
1
8
-1.09
D component of complement (adipsin) (DF)
155597
GAGGTGGGTG
1
4
-1.83
74451
CCCCAGTTGC
78
41
Apoptotic protease-activating factor (APAF) Microsomal signal peptidase subunit hmspase Complement component 5 receptor 1 (C5a ligand) (C5R1)
Calpain 4, small subunit (30K) Ubiquitin-activating enzyme E1-like
6695
TGGACTTTGT
43
37
Programmed cell death 6-interacting protein
9663
GTTGGGACAT
38
8
166468
GCGGACGAGG
38
7
-0.41
1578
CTGGCCGCTC
0
9
-0.37
77432
CCTGTAGTCC
54
24
2.31
Transforming growth factor (TGF) beta 1
1103
GGGGCTGTAT
26
12
2.18
Phospholipase A2, group IVC (cytosolic, calcium-independent) (PLA2G4C)
18858
GGCTATCTCT
6
4
1.91
CCCCAGTTGC
78
41
1.32
99491
ATGCACCCCT
6
4
1.29
184052
TGGCCATCTG
6
4
1.23
Programmed cell death 5 Baculoviral IAP repeat-containing 5 (survivin) Enzyme and signaling molecule Epidermal growth factor receptor (EGFR) alternatively spliced
Hngrc3 neurogranin RAS guanyl-releasing protein 2 (calcium and DAG-regulated) (RASGRP2) PP1201 protein (PP1201)
Kim, Jung, Seoh et al.
412
Table 5. Differential tag abundance in megakaryocytes (MKs) and non-megakaryocytes (non-MKs) (continued) Gene (Functional category)
UniGene
SAGE
Acc. No Region containing guanine nucleotide binding protein (G protein), beta 5; hypothetical protein (LOC82962) Insulin induced insig1
Tag sequence
MKs
Non-MKs
2log(MKs/non-MKs)
155090
CACCTAGGGG
6
1
1.2
56205
TATTTCAATC
6
1
1
Preproapelin Lymphocyte-specific protein 1 (LSP1) Beta-r1 putative
Microarray
56729
AGCCACCACG
6
8
-1.09
CCTACGAAAA
0
4
-1.26
103982
GAGTTACTGA
1
4
-1.17
Pim-1
81170
GTAGTATACA
35
7
0.68
Jun D
2780
ACCCCCCCGC
35
12
1.29
Jun B
198951
ACCCACGTCA
31
14
C-fos serum response element-binding transcription factor
155321
GTCACAGTCC
38
3
Glutathione peroxidase 1
76686
CTCTTCGAGA
55
122
-0.48
Glutathione S-transferase A2
89552
GAGGCCAAGA
35
108
-0.33
Glutaredoxin (thioltransferase)
28988
AAGTTTGCCT
0
12
CTCTGTTGAT
23
1
1.12
2795
TCTTGTGCAT
6
4
1.4
254105
TGAGCCTCGT
47
32
1.26
2012
TTCAATAAAA
1
41
-1.45
Heat shock 90 kD protein 1, beta
74335
GGCTCCCACT
21
0
0.39
DnaJ (Hsp40) homologue, subfamily C, member 8
74711
TCCTAGCCTG
21
4
Tubulin-specific chaperone a
24930
GCCGATCCTC
23
4
-0.23
-1
Similar to thioredoxin peroxidase (antioxidant enzyme) (homo sapiens) (LOC82852) Metabolic pathway Lactate dehydrogenase a Region containing enolase 1, (alpha); MYC promoter-binding protein 1 (LOC81977) Transcobalamin I (vitamin B12-binding protein, R binder family) (TCN1) Heat shock protein
Coagulation protein, lipoprotein, and surface antigen Major histocompatibility complex, class II, DQ alpha 1 (HLA-DQA1)
198253
TCCAGTAACA
1
4
Major histocompatibility complex, class II, DR alpha (HLA-DRA)
76807
GGGCATCTCT
1
28
-1.26
Selectin-P (granule membrane protein 140 kD, antigen CD62) (SELP)
73800
TCACCGTGGA
35
7
2.92
CD53 antigen (CD53)
82212
TCTCTCAAAG
0
4
-1.15
Apolipoprotein A-I
237658
TGTGGAGAGC
221
212
0.05
Transferrin
284176
TGTGCTGAAC
82
41
0.26
Defensin, alpha 1, myeloid-related sequence
274463
GCCTGCTATT
55
46
0.61
901
CTTTTTTCCC
23
0
CD48 antigen Each number of tags was normalized to 50,000.
expressed more highly in MKs than in non-MKs. Transcription factors, such as nuclear factor (erythroid-derived 2) 45 kD, nuclear factor (erythroid-derived 2)-like 2, and cAMP response element binding factor 2 were expressed more
highly in MKs. These transcription factors may be important in the maturation of MKs [7]. Genes related in apoptotic event as well as in mitogen-activated protein kinase (MAPK) pathway were expressed more highly in MKs. Genes encoding the
413
Hsp family, such as Hsp 90, chaperone containing TCP1, DnaJ homologue, and tubulin-specific chaperone a, were also expressed more highly in MKs. Expressions of the genes for surface antigens, such as CD48 and CD62, were higher in MKs. Validation of Genes Represented in the SAGE Analysis To verify the validity of our SAGE data, we performed a microarray experiment. Total RNA was obtained by the same way as in the SAGE experiment. This RNA was hybridized with a 10 K oligo microarray. A total of 2,807 genes found on microarray overlapped with SAGE tags. A total of 364 genes had a greater than twofold difference in expression between MKs and non-MKs and 125 genes overlapped with SAGE tags. Due to the lower sensitivity of microarray analysis, the expression ratio of some genes was underestimated (Table 5). We picked up eight genes, which were expressed differentially in MKs and non-MKs. Using RT-PCR, selected genes were evaluated in MKs and non-MKs derived from the CB of two other volunteers (Fig. 2). The results showed that β-actin was expressed almost equally in all cell types (MKs, 62 tags; non-MKs, 61 tags) studied, but apoptotic protease activating factor (MKs, 38 tags; non-MKs, 2 tags), CD48 (MKs, 23 tags; non-MKs, 0 tags), P-selectin (MKs, 35 tags; non-MKs, 7 tags), pim-1 (MKs, 35 tags; non-MKs, 7 tags), and defensin (MKs, 55 tags; non-MKs, 46 tags) were expressed more highly in MKs. The expression of KIAA0614 (MKs, 0 tags; non-MKs, 24 tags) was lower in MKs. These results validate our SAGE data for MKs and establish a general expression profile of the identified genes. DISCUSSION In this study, we investigated the global gene expression of MKs derived from human CB CD34+ cells using SAGE and microarray analyses. CB CD34+ cells were expanded with TPO, and we separated the CD41+ fraction as the MK fraction. We observed many housekeeping genes, such as ribosomal protein family genes, lipoprotein family genes, thymosin, transferrin recepFigure 2. RT-PCR analysis of genes expressed differentially in the MK and non-MK fractions. RT-PCR was performed on total RNA isolated from both fractions.
SAGE Analysis of Expanded Megakaryocytes tor, and major histocompatibility complex genes, expressed highly in both MKs and non-MKs. This result is comparable with previous results from SAGE analyses of hematopoietic cells, such as dendritic cells, monocytes, and macrophages [8-10]. However, erythroid differentiation factor, serin proteinase inhibitor, CGI-120, CGI-135, and arsenite transporter genes were expressed highly only in MKs (Tables 1 and 3). The differences in the expression levels of these genes between the two fractions suggest that these genes may play roles in the differentiation into MKs. Those genes that are already known to be involved in the differentiation and function of MKs, such as nuclear factor (erythroid derived) 45 kD, P-selectin (CD62P), platelet phosphofructokinase, coagulation factor, and megakaryocyte-associated tyrosine kinase, were expressed more highly in MKs (Tables 3 and 5). Furthermore, nuclear factor (erythroid derived) 45 kD (4.75-fold higher expression in MKs) regulates two classes of gene expression in maturating MKs that are required to reorganize the MK cytoskeleton and initiate proplatelet formation [7]. cAMP-responsive element-binding protein-like 1, which is the binding partner of nuclear factor (erythroid derived) 45 kD, was also expressed highly in MKs (38-fold higher in MKs than in non-MKs). In particular, many immediate-early genes, such as c-fos, c-jun, and d-jun, which propagate the cellular response to growth stimuli, were expressed more highly in MKs. These transcription factors may influence MK-specific gene expression.
Kim, Jung, Seoh et al. In contrast, the levels of expression of cytoskeletal protein-coding genes, such as actin-binding proteins and tubulin family genes, were similar in both fractions. But many of the ion-channel composing protein-coding genes, such as transportin, TAP, purinergic receptor P2X, and arcenite receptor, were expressed highly in MKs (Tables 3 and 5). Nevertheless, P-selectin, one of the adhesion molecules, had a fivefold higher expression in MKs (Table 5, Fig. 2). P-selectin could mediate megakaryocyte-fibroblast interactions. Interaction between MKs and fibroblasts regulates the production of proplatelets and their migration into the sinusoidal lumina [11, 12]. Apoptotic-related genes, such as transforming growth factor beta 1 (TGF-β1), calpain, programmed cell death interacting protein, and APAF, were predominantly expressed in MKs. However, the expression of survivin, an inhibitor of apoptosis, was low in MKs. These results are consistent with our previous report that TPO-induced apoptosis was closely associated with megakaryocytic differentiation [5]. TGF-β1, which was highly expressed in MKs (twofold greater than in non-MKs), plays a pivotal role in the control of differentiation, proliferation, and the state of activation of many different cell types, including immune cells [13]. The molecular mechanisms involved in these apoptotic processes seem to involve the activation of the SMAD protein family [14]. The TGF-β1 receptor initiates intracellular signaling through the activation of SMAD proteins, and specific SMAD proteins become phosphorylated and associate with other SMAD proteins. These heteromeric SMAD complexes accumulate in the nucleus, where they modulate the expression of target genes. Only the relationship between TGF-β1 and SMAD 4 is known in apoptosis [15]. SMAD 3 and 4 together could enhance TGF-β1-mediated transactivation. Moreover, the (JNK) pathway was shown to be activated by SMAD proteins in TGF-β1induced apoptosis [16]. In Tables 3 and 5, the mad 4 homologue, SMAD- and olf-interacting protein genes, and JNK-related proteins, such as c-jun and c-fos, were more highly expressed in MKs. Calcium-dependent protease and calpain-1 and 4 which are generally associated with necrosis and some forms of TGF-β1-induced apoptosis [17], were expressed highly in MKs (over twofold greater than in nonMKs),. Apoptosis might be controlled by TGF-β1 and SMAD pathways in MKs. As confirmed by RT-PCR (Fig. 2), the expression of APAF was 19-fold higher in MKs than in non-MKs (Table 5). APAF is important in cell death machinery (apoptosome) and is involved in different apoptotic pathways in different states. In apoptotic conditions, caspases are often activated by APAF-1 apoptosome, a complex formed in response to many death-inducing stimuli [18, 19]. Activation
414
of caspases is regulated directly or indirectly by antiapoptotic members of the Bcl-2 and inhibitor of apoptosis protein (IAP) family, like survivin [20, 21]. As an antiapoptotic protein, survivin inhibits caspases 3 and 7. In the present study, the expression of survivin was lower in MKs (ninefold). By contrast, stress-induced transcripts, such as some of the Hsp, were markedly greater in MKs. It has been reported that Hsp 90 has proapoptotic and antiapoptotic dual controversial potentials [22]. Expression of the Hsp 90 gene was 20-fold higher in MKs than in non-MKs. Thus, the higher expression of APAF and Hsp 90 and lower expression of survivin may contribute to the apoptotic process of MKs. Binding of TPO to its receptor, c-Mpl, results in the activation of a variety of signaling molecules that include components of the Ras/MAPK pathway [23-25] and Janus kinase-signal transducer and activator of transcription (JAK/STAT) pathway [26]. In the present study, the genes encoding proteins related to the Ras/MAPK pathway, such as protein kinase C (PKC)-like protein, PKC substrate 80 K-H, epidermal growth factor (EGF) response factor 2, neuroblastoma RAS viral homologue, and MAP kinase kinase kinase 2, were expressed more highly in MKs. These results are consistent with the previous report that the Ras/MAPK pathway contributes to TPO-induced differentiation. Recently, it was reported that PKC activation was essential for proplatelet formation [27]. However, the JAK and STAT families, which are related to the cytokine-signaling pathway and MK proliferation, were only detected in either MKs or non-MKs. Pim-1, another Ser/Thr kinase was expressed more highly in MKs, as much as fivefold higher than in non-MKs (Fig. 2). It has been reported that the expression of pim-1 was involved in MK development [28]. Although the function of pim-1 is obscure, it might perform as a survival factor in eosinophil apoptosis [29]. These apoptotic factors and survival factors might participate in MK development cooperatively. Interestingly, CD 48 was predominantly expressed in MKs (23-fold greater than in non-MKs, Fig. 2). It is a highaffinity ligand of 2B4 (CD244), expressed on natural killer (NK) or T cells. The interaction between CD244 and CD48 may play an important role in the regulation of NK and T cells [30]. Antimicrobial peptide, azurocicin (expressed 1.3-fold higher in MKs) and defensin (expressed 1.5-fold higher in MKs, Fig. 2) were two of the antibacterial peptides. They have a chemotactic effect on mononuclear cells and neutrophils, and induce T-cell migration for direct bacterial activity [31]. MKs might interact with NK cells or T cells through CD48 and, through secretion of azurocidin and defensin, might play the role of activator of mononuclear cells. In summary, we identified the genes expressed differentially in MKs and non-MKs derived from human CB CD34+
415
cells by ex vivo expansion using TPO. The expression levels of several genes in apoptosis, such as APAF and calpain were higher in the MK fraction. Interestingly, azurocidin and defensin, known as antibacterial peptides, were highly expressed in MK cells. In contrast, the expression of survivin, an antiapoptotic protein, was lower in the MK fraction. These gene expression data from SAGE analyses may provide
SAGE Analysis of Expanded Megakaryocytes useful information on MK maturation, platelet production, and the possibility of interaction with other blood cells. ACKNOWLEDGMENT This study was supported by a grant from the Korea Health 21 R&D Project, Ministry of Health & Welfare, Republic of Korea (HMP-00-CH-04-0004).
R EFERENCES 1 Tao H, Gaudry L, Rice A et al. Cord blood is better than bone marrow for generating megakaryocytic progenitor cells. Exp Hematol 1999;27:293-301. 2 Falcieri E, Bassini A, Pierpaoli S et al. Ultrastructural characterization of maturation, platelet release, and senescence of human cultured megakaryocytes. Anat Rec 2000;258:90-99. 3 Piacibello W, Sanavio F, Garetto L et al. Extensive amplification and self-renewal of human primitive hematopoietic stem cells from cord blood. Blood 1997;89:2644-2653. 4 Seoh JY, Woo SY, Im SA et al. Distinct patterns of apoptosis in association with modulation of CD44 induced by thrombopoietin and granulocyte-colony stimulating factor during ex vivo expansion of human cord blood CD34+ cells. Br J Haematol 1999;107:176-185. 5 Ryu KH, Chun S, Carbonierre S et al. Apoptosis and megakaryocytic differentiation during ex vivo expansion of human cord blood CD34+ cells using thrombopoietin. Br J Haematol 2001;113:470-478. 6 Velculescu VE, Zhang L, Volgelstein B et al. Serial analysis of gene expression. Science 1995;270:484-487. 7 Shivdasani RA. Molecular and transcriptional regulation of megakaryocyte differentiation. STEM CELLS 2001;19:397-407.
14 Ten Dijke P, Goumans MJ, Itoh F et al. Regulation of cell proliferation by Smad proteins. J Cell Physiol 2002;191:1-16. 15 Simeone DM, Zhang L, Graziano K et al. Smad4 mediates activation of mitogen-activated protein kinases by TGF-beta in pancreatic acinar cells. Am J Physiol Cell Physiol 2001;281:C311-C319. 16 Atfi A, Djelloul S, Chastre E et al. Evidence for a role of Rholike GTPases and stress-activated protein kinase/c-Jun N-terminal kinase (SAPK/JNK) in transforming growth factor beta-mediated signaling. J Biol Chem 1997;272:1429-1432. 17 Gressner AM, Lahme B, Roth S. Attenuation of TGF-betainduced apoptosis in primary cultures of hepatocytes by calpain inhibitors. Biochem Biophys Res Commun 1997;231:457-462. 18 Almond JB, Snowden RT, Hunter A et al. Proteasome inhibitorinduced apoptosis of B-chronic lymphocytic leukaemia cells involves cytochrome c release and caspase activation, accompanied by formation of an approximately 700 kDa Apaf-1 containing apoptosome complex. Leukemia 2001;15:1388-1397. 19 Bratton SB, Cohen GM. Apoptotic death sensor: an organelle’s alter ego? Trends Pharmacol Sci 2001;22:306-315. 20 Altieri DC, Marchisio PC, Marchisio C. Survivin apoptosis: an interloper between cell death and cell proliferation in cancer. Lab Invest 1999;79:1327-1333.
8 Hashimoto S, Suzuki T, Dong HY et al. Serial analysis of gene expression in human monocytes and macrophages. Blood 1999;94:837-844.
21 Baccini V, Roy L, Vitrat N et al. Role of p21(Cip1/Waf1) in cell-cycle exit of endomitotic megakaryocytes. Blood 2001;98:3274-3282.
9 Hashimoto S, Suzuki T, Dong HY et al. Serial analysis of gene expression in human monocyte-derived dendritic cells. Blood 1999;94:845-852.
22 Garrido C, Gurbuxani S, Ravagnan L et al. Heat shock proteins: endogenous modulators of apoptotic cell death. Biochem Biophys Res Commun 2001;286:433-442.
10 Hashimoto SI, Suzuki T, Nagai S et al. Identification of genes specifically expressed in human activated and mature dendritic cells through serial analysis of gene expression. Blood 2000;96:2206-2214.
23 Whalen AM, Galasinski SC, Shapiro PS et al. Megakaryocytic differentiation induced by constitutive activation of mitogenactivated protein kinase kinase. Mol Cell Biol 1997;17:19471958.
11 Wickenhauser C, Schmitz B, Baldus SE et al. Selectins (CD62L, CD62P) and megakaryocytic glycoproteins (CD41a, CD42b) mediate megakaryocyte-fibroblast interactions in human bone marrow. Leuk Res 2000;24:1013-1021.
24 Drachman JG, Sabath DF, Fox NE et al. Thrombopoietin signal transduction in purified murine megakaryocytes. Blood 1997;89:483-492.
12 Becker RP, De Bruyn PP. The transmural passage of blood cells into myeloid sinusoids and the entry of platelets into the sinusoidal circulation; a scanning electron microscopic investigation. Am J Anat 1976;145:183-205.
25 Minamiguchi H, Kimura T, Urata Y et al. Simultaneous signalling through c-mpl, c-kit and CXCR4 enhances the proliferation and differentiation of human megakaryocyte progenitors: possible roles of the PI3-K, PKC and MAPK pathways. Br J Haematol 2001;115:175-185.
13 Schuster N, Krieglstein K. Mechanisms of TGF-beta-mediated apoptosis. Cell Tissue Res 2002;307:1-14.
26 Miyazaki R, Ogata H, Kobayashi Y. Requirement of thrombopoietin-induced activation of ERK for megakaryocyte
Kim, Jung, Seoh et al. differentiation and of p38 for erythroid differentiation. Ann Hematol 2001;80:284-291. 27 Maulon L, Mari B, Bertolotto C et al. Differential requirements for ERK1/2 and P38 MAPK activation by thrombin in T cells. Role of P59Fyn and PKC epsilon. Oncogene 2001;20:1964-1972. 28 Doshi PD, Giri JG, Abegg AL et al. Promegapoietin, a family of chimeric growth factors, supports megakaryocyte development through activation of IL-3 and c-Mpl ligand signaling pathways. Exp Hematol 2001;29:1177-1184.
416
29 Temple R, Allen E, Fordham J et al. Microarray analysis of eosinophils reveals a number of candidate survival and apoptosis genes. Am J Respir Cell Mol Biol 2001;25:425-433. 30 Boles KS, Stepp SE, Bennett M et al. 2B4 (CD244) and CS1: novel members of the CD2 subset of the immunoglobulin superfamily molecules expressed on natural killer cells and other leukocytes. Immunol Rev 2001;181:234-249. 31 Chertov O, Yang D, Howard OM et al. Leukocyte granule proteins mobilize innate host defenses and adaptive immune responses. Immunol Rev 2000;177:66-78.