Glia Maturation Factor Gamma (GMFG): A Cytokine-Responsive
Protein During Hematopoietic Lineage Development and Its F'unc-
t ional Genomics Analysis
Ying Shil*, Ling Chen', Lance A. Liotta2#, Hong-Hui Wan3, and Griffin P. Rodgersl*
Molecular and Clinical Hematology Branch, National Institute of Diabetes and Digestive and Kidney Diseases
(NIDDK), National Institutes of Health (NIH), Bethesda, MD 20892-1822, USA; Laboratory of Pathology,
National Cancer Institute, NIH, Bethesda, MD 20892-7412, USA; Maryland Institute of Genomics and De-
partment of Computer Science, University of Maryland, Silver Spring, MD 20906, USA.
Current address: The Center for Applied Proteomics and Molecular Medicine, George Mason University,
Manassas, VA 201 10, USA.
Human hematopoiesis was evaluated using the techniques of controlled stem
cell differentiation, two-dimensional gel electrophoresis-based proteomics, and
functional genomics. We provide the first report that glia maturation factor
gamma (GMFG) is a cytokine-responsive protein in erythropoietin-induced and
granulocyte-colony stimulating factor-induced hematopoietic lineage development.
Results from global functional genomics analysis indicate that GMFG possesses
several other features: hematopoietic tissue-specific gene expression, a promoter
concentrated with high-score hematopoiesis-specif ic transcription factors, and pos-
sible molecular coevolution with a rudimentary blood/immune system. On the
basis of our findings, we hypothesize that GMFG is a hematopoietic-specific pro-
tein that may mediate the pluripotentiality and lineage commitment of human
hematopoietic stem cells.
Key words: GMFG, hematopoiesis, proteomics, functional genomics
Although it is widely accepted that the hematopoi-
etic stem cell (HSC) is capable of both se!f-renewal
and differentiation into all of the peripheral blood cell
types, the mechanisms that control these self-renewal
and differentiation processes remain a mystery (1,2).
To address this issue, we developed a special cul-
ture system in which HSCs cultured for 14 days wiih
erythropoietin (EPO) were recultured for another 14
days with granulocyte-colony stimulating factor (G-
CSF) and vice versa (that is, G-CSF-stimulated HSCs
were recultured with EPO). This unique culture sys-
tem provides both practical and theoretical platforms
for further study in this area. Using this culture
system, we observed phenotypic lineage interconver-
sion between erythroid and myeloid cells derived from
human hematopoietic AC 133+ st em/progeni tor cells
Geno. Prot. Bioinfo.
To focus on the molecular aspects of
hematopoiesis, we used proteomics and bioinformat-
ics to further investigate lineage development and
interconversion. Upon analysis of protein profiles
from two-dimensional gel electrophoresis (2-DE), we
discovered a protein spot that was responsive to
specific cytokine signals that determine the forma
tion of specific blood cell lineages. Using liquid
chromatography-tandem mass spectrometry (LC-
MS/MS), the protein was identified as glia mat-
uration factor gamma (GMFG). Later, the cDNA
sequence of the GMFG gene was confirmed using
the reverse transcriptase-polymerase chain reaction
The GMFG gene, also called the glia maturation
factor beta homolog (GMFB-h) gene, was first re-
ported by two groups in 1998 (4,5). Mao et al (4)
discovered the GMFG gene when sequencing cDNAs
from CD34+ hematopoietic stem/progenitor cells.
Asai et a1 (5) found the gene inadvertently when con-
ducting a Northern blot experiment on GMFB in as-
Vol. 4 No. 3 2006
GMFG and Hematopoiesis
trocytes. The full-length cDNA of GMFG is approx-
imately 0.9 kb and encodes a protein of 142 amino
acids. Results of an enzyme-linked immunoassay in-
dicate that the GMFG gene is highly expressed in
spleen, thymus, colon, and lung (6). GMFG has also
been found in human serum at various ages; it was
highly expressed in 21- to 30-year-old individuals and
began to decrease rapidly in individuals older than 30
years (6). In a previous study, the promoter analysis
identified certain binding sites for transcription fac-
tors (TFs) that were reported to be closely related to
hematopoiesis ( 7).
Although the function of GMFG remains unclear,
another member of the same protein family, GMFB,
has been well studied. GMFB is also a protein of
142 amino acids and was initially identified as a
growth/differentiation factor from vertebrate brains
(8-12). This protein has several serine/threonine
(Ser/Thr) phosphorylation sites and can be phospho-
rylated with protein kinase A (PKA), protein kinase C
(PKC), casein kinase I1 (CKII), and p90 ribosomal S6
kinase (RSK) (13). The PKA-phosphorylated GMFB
is a potent inhibitor of extracellular signal-regulated
kinases 1 and 2 (ERKl/ERK2) and is a strong en-
hancer of p38 (14,15). Both ERKl/ERK2 and p38
belong to the same mitogen-activated protein kinase
(MAPK) family. Thus, GMFB was considered to be
a putative intracellular kinase regulator (16) and a
modulator of intracellular signal transduction via its
phosphorylation (6). In addition, a previous report
suggested that GMFB may have played an important
role in maintaining stem cell systems as they devel-
oped during early metazoan evolution ( I 7).
Here we provide a comprehensive bioinformatic
analysis of GMFG, including promoter analysis, tis-
sue/cell distribution analysis, and molecular evolu-
tionary/phylum analysis using available DNA mi-
croarray data banks. Our results support the hy-
pothesis that GMFG may play an important role as a
maintenance factor for HSC and as a regulation factor
for hematopoietic lineage commitment.
A cytokine-responsive protein in EPO-
and G-CSF-induced HSC differentiation
As shown in a previous report of our unique cul-
ture system (3), we cultured AC133+ human HSCs
with EPO for 14 d, which resulted in a definite
146 Geno. Prot. Bioinfo.
erythroid-lineage cell population that we termed El4
cells (Figure 1A). Simultaneously, we cultured addi-
tional AC133+ cells with G-CSF for 14 d, which re-
sulted in a definite myeloid-lineage cell population
that we termed G14 cells (Figure 1C). When the El4
and G14 samples were analyzed by 2-DE, we found
an interesting protein spot that exhibited an approx-
imately 10-fold difference in density between the ery-
throid and myeloid cell populations. This protein was
present in untreated AC133+ cells, termed D O cells.
Its expression decreased with EPO stimulation and
increased slightly with G-CSF stimulation (Figure 1B
and D, respectively). Furthermore, when we recul-
tured the El4 cells with G-CSF for another 14 d,
the erythroid cells switched to a myeloid cell popula-
tion termed E14+G14, in which the protein spot in-
creased (Figure 1E). Conversely, when we recultured
the G14 cells with EPO for another 14 d, the myeloid
cells switched to an erythroid cell population termed
G14-+E14, in which the protein spot decreased (Fig-
ure 1E). Therefore, the cytokine-responsive character
of this protein can be seen not only in HSCs but also
in El4 erythroid cells and G14 myeloid cells. The
latter observation is important because it may set up
a molecular basis for the lineage switch that we ob-
served in earlier research (9).
Upon repeating 2-DE on G14 samples, we manually
excised and collected the gel spots and analyzed the
proteins by LC-MS/MS analysis (Tables 1 and 2). We
used GMFB as a reference and thoroughly compared
the peptide sequences identified by MS. The peptide
difference between GMFG and GMFB permits us to
finally identify our protein as GMFG (Figure 2A).
At the level of transcription, an RT-PCR validation
of the results was performed with both the erythroid
and myeloid lineages (Figure 2B).
Differential expression of GMFG only
observed at the protein level
After Zhang et al (18) reported the GMFG gene as
one of the new genes expressed in CD34+ HSCs, they
designed a gene chip experiment to investigate the
transcription of 300 new genes in various hematopoi-
etic cell lines, including NB4, HL60, U937, K562, and
Jurkat. Their results revealed no differential expres-
sion of the GMFG gene among these cell lines (18).
Vol. 4 No. 3 2006
Shi et al.
Fig. 1 A protein spot showing differential expression between erythroid and myeloid lineages. A and C . Morphology
of erythroid and myeloid cells, respectively. B and D. 2-DE of erythroid and myeloid cells, respectively. The protein
spot of interest is indicated by the arrow in the enlargements of the 2-D gels. E. Normalized intensity value of the
protein spot as it changed during lineage development and switching. The five cell populations, indicated by DO, E14,
G14, E14&+G14, and G14jE14, are defined in Materials and Methods.
Fig. 2 The protein spot of interest was identified as GMFG. A. Protein sequence alignment for GMFG and GMFB.
Amino acid differences are underlined within the fragments that were identified by MS in this study. GMFG was
confirmed by this comparison. B. Comparisons of the GMFG mRNA level and its corresponding protein level during
lineage differentiation. Three cell population samples were collected: D O for AC133+ hematopoietic stem/progenitor
cells, El4 for erythroid cells, and G14 for myeloid cells (see Materials and Methods). The mRNA was evaluated by
RT-PCR and the protein was evaluated by 2-DE. For comparison, both the mRNA value and the protein value of D O
were normalized to 1.0. All other values were displayed proportionally.
Geno. Prot. Bioinfo.
Vol. 4 No. 3
GMFG and Hematopoiesis
Table 1 The General Information from LC-MS/MS Data
glia maturation factor
Total score Mass (Da) PI
Database Percentage covered
26.06% 5.1 NCBI (Human)
Table 2 Precursor Mass and Ion Score for Each of the Three Peptides Identified by LC-MS/MS
68 - 81
111 - 122
59 - 67
In the studies herein, our RT-PCR results also demon-
strated that the GMFG gene was not significantly
differentially expressed between El4 erythroid and
G14 myeloid cells (Figure 2B). However, at the level
of protein expression, GMFG exhibited a greater than
10-fold difference (Figure 1). The results of many re-
searchers who have conducted simultaneous gene ex-
pression and proteomic studies confirm the fact that
only a small percentage of genes show a statistically
significant correlation between the expression levels
of their corresponding mRNAs and proteins (19). It
is widely accepted that the primary cause of the dis-
crepancy between gene and protein expression is the
post-translational modification of proteins. In our re-
search, we noticed that GMFG is a protein with six
consensus phosphorylation sites ( I 6). An experiment
is planned to evaluate the potential contributions of
post-translational modifications of GMFG to our 2-
DE results and to cell lineage formation. The results
presented herein provide another example support-
ing the inevitable trend of researchers to approach a
biomedical problem with the combined, comprehen-
sive techniques of genomics, proteomics, and bioin-
Recently, gene profile-based studies of the molecu-
lar signature of stem cells (2,2U) have revealed valu-
able information; however, results from our experi-
ments suggest that the’ “total picture” might not be
obtained until the protein profile is completed. It may
not be surprising to find considerable inconsistencies
between the gene signature and the protein signature
within the same stem cell.
No significant GMFB transcription was observed
for both lineages at 28 days’ scale (Figure 3). The
536-bp cDNA product of the RT-PCR wits sequenced
and confirmed to be GMFG (data not shown). The
GMFG gene expression profiling is displayed in Fig-
ure 4. The results of GMFG promoter analysis are
Geno. Prot. Bioinfo.
demonstrated in Figure 5, and the GMFG’s molecu-
lar evolutionary analysis is shown in Figure 6.
Possible mechanism of GMFG respon-
siveness to cytokines
The mechanism of GMFG responsiveness to HSC cy-
tokines and its involvement in regulating HSC differ-
entiation remains unknown. From previous research
on GMFB, we know that the PKA-phosphorylated
form of GMFB potently inhibits ERKl/ERK2 and
strongly enhances p38 (I4,15). These findings led
us to consider the possibility that phosphorylation/
dephosphorylation may be involved in the mechanism
by which GMFG regulates HSC differentiation. Be-
cause GMFG and GMFB have the same Ser/Thr
phosphorylation molecular characteristics, it is as-
sumed that the major cellular biochemical activities
of these two proteins will be similar (21). It has been
well documented that during hematopoiesis, Ser/Thr
phosphorylation plays an important role in signal
transduction in HSC differentiation and proliferation.
For example, both the inhibition of MAP1/2 (22)
and the enhancement of p38 (23) can increase ery-
thropoiesis. PKA-phosphorylated GMFB is known
to be an inhibitor of MAP1/2 and an enhancer of p38
(14,15), and there is evidence that PKA is involved
in erythropoiesis (24 ). We have begun experiments
to investigate the roles of GMFG in these processes.
GMFG and hematopoietic development
By using a global bioinformatics profiling strategy, we
collected all accessible microarray data about GMFG
Vol. 4 No. 3 2006
Shi et al.
Fig. 3 Validation of GMFG by RT-PCR. A. RT-PCR results for GMFG and GMFB during erythroid differentiation
induced by EPO. Samples were collected at 0, 7, 14, 21, and 28 d, respectively. B. RT-PCR results for GMFG and
GMFB during myeloid differentiation induced by GCSF. Samples were collected at 0, 7, 14, 21, and 28 d, respectively.
gene expression. The expression level distribution of
the GMFG gene in human tissues and cell lines is
shown in Figure 4. It can be seen that the GMFG
gene is highly expressed in blood (including in myeloid
leukemia and lymphoid leukemia cell lines), thymus,
spleen, fetal liver, and lung. It is noteworthy that
most of the tissues with high levels of GMFG expres-
sion are related to the blood and immune systems.
The distribution pattern is consistent with the re-
sults of our recent Northern blot experiment (data
not shown) and is also very similar to the findings
of a recent study that used immunoassays to deter-
mine the distribution of the GMFG protein (6). O u r
bioinformatics data also indicates that the expres-
sion of the GMFG gene in nervous/brain tissue is not
higher than that in any other tissue, which confirmed
Walker’s finding (25), and thus the expression distri-
bution pattern of the GMFG gene differs from that
of the GMFB gene. It is interesting to note that
the Burkitt’s lymphoma cell line Daudi differs greatly
from the Burkitt’s lymphoma cell line Raji with re-
spect to GMFG gene expression (Figure 4), with the
Geno. Prot. Bioinfo.
latter cell line having a much lower level of expression
of the GMFG gene.
High-score hernatopoietic TF binding sites of
the GMFG promoter
The continual replacement of blood cells is essential
for vertebrates. This process is largely dependent on
hematopoietic, lineage-specific TFs (26). We evalu-
ated the 750-bp GMFG promoter region for TF bind-
ing sites using our new scoring system. By setting
a threshold score of 0.900, we found 20 putative TF
binding sites with scores ranging from 0.900 to 1.000
(Figure 5). Among these high-score sites, there are
three GATA-1 binding sites, with scores of 0.902,
0.906, and 0.963, respectively; one GATA-2 binding
site, with a score of 0.921; two GATA-3 binding sites,
with scores of 0.909 and 0.922, respectively; two AML-
la (27) binding sites, each with a perfect score of
1.000; three MZFl (28) binding sites, with scores of
0.904, 0.930, and 0.957, respectively; one Lyf-1 bind-
ing site, with a score of 1.000; and one c-Ets-1 binding
Vol. 4 No. 3 2006 149
GMFG and Hematopoiesis
Fig. 4 Global GMFG gene expression profile.
site, with a score of 0.922. All of these TFs are related
to erythroid, myeloid, T cell, and B cell differentiation
and proliferation. In particular, AML-la is considered
to be a critical (master) regulator of hematopoietic
cell development (27). Many hematopoiesis-specific
genes are activated by AML-la, including interleukin-
3, granulocyte-macrophage-colony stimulating factor
(GM-CSF), CSF-lR, and the T cell receptor (27).
AML-la may also be involved in HSC maintenance
and renewal (26). Its tissue-specific expression oc-
curs mostly in thymus and spleen (29), which is con-
sistent with the tissue specificity expression of the
GMFG gene, indicating that the latter might be a
downstream regulator for AML-la.
GMFG protein coevolved with increasing com-
plexity of the blood/immune system
In addition to the GMFGs from human, mouse, and
rat that were reported by others (16), we have de-
tected the protein sequences of GMFG in chimpanzee,
monkey, pig, and cow using our GeneKey software.
We also detected GMFs in frog, zebrafish, the spotted
green pufferfish Tetraodon nigroviridis, the filarial
worm Brugia malayi, mosquito, and the nematode
Caenorhabditis briggsae. GMF in the sponge was re-
ported by Muller et al (17). Selected multiple se-
quence alignments are shown in Figure 6A. From an
evolutionary perspective, we can see that GMF genes
that exist in Metazoa probably originated via dupli-
cation of the actin-depolymerizing factor (ADF) gene
(data not shown). Late in the evolution of the Ver-
tebrata, we find the two family members GMFG and
GMFB. Using our Sandwich Sequence Alignment soft-
ware, we also found a GMF in the carp (Cyprinvs
carpio) (30) that is very similar to human GMFB
and GMFG, with slightly more similarity to GMFG
(Figure 6B). This observation might imply that ani-
mals of the early stages of vertebrate evolution may
have a single GMF protein that shares the functions
of GMFB and GMFG for development of the nervous
system and the blood/immune system. As the com-
plexity of the nervous system and the blood/immune
system increased in the later stages of vertebrate
evolution, especially in mammals, it is conceivable
that the single GMF gene was duplicated and subse-
quently modified to give rise to the GMFB gene and
the GMFG gene. The observation may provide one
possible explanation for why the overlapping genes,
when comparing the stem cell molecular signatures,
are “negligible” among HSCs, neural stem cells, and
embryonic stem cells (31). It seems that different
members of the same gene family are preferentially
expressed in different systems/tissues to perform vir-
tually the same task. Although these members are
structurally and functionally similar, they have dis-
tinct characteristics in cDNA microarray analysis.
There are two primary features of HSCs: (1) their
ability to replicate without differentiation, and (2)
their ability to differentiate, under specified condi-
tions, to become different types of blood cells. Be-
cause GMFG (both the mRNA and proteiu forms) is
present in HSCs and exhibits a differential pattern at
150 Geno. Prot. Bioinfo. Vol. 4 No. 3
Shi et al.
Entry TF Score
-740 CTTTTCCAGC CCTGCAATTC AAATATCCCA GATGGGGGTA AATCTAGGAA
MOO083 MZFl 0.330
-690 GGCCACCTGG AGGAGGGGAG GAGCAAAATA GTTCGTTTTT AGTACCTATT
- - -____
-640 GTGTCTGCCA TGCTGGCAGC TATGTGAAGC TATTTATTTA TTTATTTTTA
-590 TTTATTTGTA TTTTTATTGC CTGGGATAGA GTGCAATGAT GTGATCTTGG
-540 CTCACTGCAA CCTCTGCTGC TCGGATTCAA GCAATTCTTG TGCCTCAGAC
-490 TCCCGAGTAG CTGGGATCAC AGGCGTGCAC CACCATGCCA GGCTAATATT
-440 TTGTATTTTT AGTAGAGATG GGGTTTTGCC ATGTTGGTCA GGCTGGTCTC
-390 CAACTCCTGA CCTCAGGTGA TCCGCCCGCC TCGGCCTCCC ARAGTGCTGG
MOO076 GATA-2 0.921
MOO075 GATA-1 0.906
MOO073 deltaE 0.926
MOO220 SREBP-1 0.310
-340 CATTACAGGT GTGAGCCACC ATGCCCGGCC GATGTGAAGC TATTTATATC
-290 CTCACCACAA TCTCAAATCA GAGGGGTGAA GTTACTTAGC TAGGGTCACA
-240 CAGCAAGGAA GCTTTGGAAC CCTGGTCTGA GCGATTTCCT GACAGGTCCT
-190 GGCAGATGAG GGGAAGGAAG GAGGGGGAGG AGCCCTCTGT GACAGTTGTC
-- - - __- -
-140 CCAGAAAGGG CATAAACAGG ATGTGGTGTT GGATGAAACC TTCCTCCTAC
-90 TGCACAGCCC GCCCCCCTAC AGCCCCGGTC CCCACGCCTA GAAGACAGCG
M00083 MZFl 0.904
MOO271 AML-la 1.000
M00083 MZFl 0.357
-40 GAACTAAGAA AAGAAGAGGC CTGTGGACAG AACAATCATG
- - ---__-
Potential Functionflissue SDecific
myeloid development, tumor/gmwth suppressor
in the hematopoietic compartment
hematopoiesis, erythroid development
regulates T cell TCR delta gene
early stage of B and T cell development
regulating angiogenesis in response to VEGF
mediator of FGF to initiate Hox gene
master regulator of hematopoiesis
see AML-1 a
T cells development, may play role in organ formation
activator, most abundant in thymus and spleen
cofactor of horneo domain protein in ALL
Fig. 5 Results of GMFG promoter analysis. Only 20 high-score putative TFs were reported. A brief description of TF
potential function/tissue location is provided. TCR, T cell receptor; VEGF, vascular endothelial growth factor; FGF,
fibroblast growth factor; ALL, acute lymphoblastic leukemia.
the protein level during lineage commitment, and also
based on our functional genomics analysis, we hypoth-
esize that GMFG plays roles in both features of HSCs.
That is, GMFG might function to maintain HSCs in
a self-renewing precursor state, and it might also act
as a lineage regulator for hematopoiesis. Various pro-
tein modifications, such as phosphorylation and de-
phosphorylation, might provide the mechanism(s) by
which GMFG performs these different functions.
Materials and Methods
We used a liquid culture system that has been pre-
viously described (3) for studying erythroid and
myeloid differentiation of human CD133+ bone mar-
row stem cells. The procedure was modified slightly
in that GM-CSF was added along with EPO into
the erythroid culture system to better study the
effect of EPO versus G-CSF on the differentiation
and interconversion between erythroid and myeloid
lineages in vitro. Briefly, normal human CD133-
selected bone marrow stem cells were seeded in ery-
Geno. Prot. Bioinfo.
throid and myeloid culture systems. EPO was used
for erythroid-specific differentiation and G-CSF was
used for myeloid-specific differentiation in the pres-
ence of other cytokines, such as stem cell factor
(SCF, 50 ng/mL), interleukin-3 (IL-3,lO ng/mL), and
GM-CSF (10 ng/mL) for both cell culture systems.
CD133+ stem cells (DO) were grown for 14 d in the
erythroid culture system with EPO (E14) or in the
myeloid culture system with G-CSF (G14). El4 cells
were then recultured for another 14 d in the medium
containing G-CSF (E14-G14), and G14 cells were
recultured for 14 d in the medium containing EPO
(G14-El4). Control cells were grown in the medium
free of cytokines. Samples from each cell population
were stained with the Wright-Giemsa stain.
From each cell culture, the cell pellet (about 1x106
cells) was dissolved in a cell lysis buffer consisting
of 8 M urea, 2% (vol/vol) 3-[(3-cholarnidopropyl)-
dimethylammonio]-propane sulfonate (CHAPS), and
1% (wt/vol) dithiothreitol (DTT). Approximately 10
pg of protein was rehydrated overnight in a volume
of 200 mL of 0.5% (vol/vol) CHAPS, 15 mM DTT,
Vol. 4 No. 3 2006
GMFG and Hematopoiesis
Fig. 6 Molecular evolutionary analysis of GMFG. A. Amino acid sequence alignment of GMFG for selected species.
For certain species, the protein is indicated as “GMF” instead of “GMFG” because only one GMF gene has been
identified in these species. B. The result of Sandwich Sequence Alignment used for GMF of carp (Cyprinus carpio).
The green color indicates the identical residues between carp GMF and human GMFB. The red color indicates identical
residues between carp GMF and human GMFG. The yellow color indicates residues shared by all three proteins. “+”
indicates residues that are identical between human GMFB and GMFG, but differ from carp GMF.
0.5% (vol/vol) IPG buffer, pH 4-7, in a Reswelling
Tray ( Amersham Bioscience, Uppsala, Sweden) on
an 11-cm, pH 4-7 IPG strip (Immobiline DryStrip;
Amersham Bioscience) . Isoelectric focusing of sam-
ples was performed on a Multiphor I1 Electrophore-
sis Unit (Amersham Bioscience) for 45,000 Vh us-
ing the following protocol: 30 min at 150 V, 1 h at
300 V, 1 h at 1,500 V, and 12 h 20 min at 3,500
V. Subsequently, IPG strips were equilibrated for 15
min in equilibration buffer [6 M urea, 30% (wt/vol)
152 Geno. Prot. Bioinfo.
glycerol, 2% sodium dodecyl sulfate (SDS) in 0.05 M
Tris-HC1 buffer, pH 8.81 containing 1% (wt/vol) DTT
and 0.001% (wt/vol) bromophenol blue. Next, IPG
strips were equilibrated for 15 min in the equilibra-
tion buffer containing 250 mM iodoacetamide.
IPG strips were further processed for second-
dimension polyacrylamide gel electrophoresis on Ex-
celGel SDS XL 12-14 according to procedures recom-
mended by the manufacturer (Amersham Bioscience).
ExcelGels were silver-stained with Hoefer Processor
Vol. 4 No. 3
Shi et al.
Plus automatic stainer according to the protocol pro-
vided by the manufacturer (Amersham Bioscience).
2-DE1 image analysis
Scanning of gels was performed on a BioRad GS-800
Calibrated Imaging Densitometer (BioRad, Veenen-
daal, Netherlands). Scanned TIFF images were ana-
lyzed using PDQuest 2D Gel Analysis Software ver-
sion 7.0 (BioRad). Spots were automatically detected
and images were checked by eye for undetected or in-
correctly detected spots. Both spot volume and nor-
malized spot volume datasets were used for further
analysis. Average gels were obtained using the Cre-
ate Average Gel Option of the software.
Protein identification by MS
Silver-stained gel spots were destained, and individ-
ual protein gel spots were subjected to reduction
and alkylation, followed by a n situ digestion with
sequencing-grade modified trypsin (Promega, Madi-
son, USA). Peptides from in-gel digests were ana-
lyzed by capillary LC-MS/MS and matrix-assisted
laser desorption/ionization (MALDI). A nano high-
performance liquid chromatography system (LC
Packings Inc., San Francisco, USA) with a F’usica col-
umn (0.075~150 mm; packed with PepMapTMC18, 5
pm, 1OOA; LC Packings, Inc.) was interfaced to a QS-
TAR mass spectrometer (Applied Biosystems, Foster
City, USA). Peptides were eluted with a 10-min gradi-
ent of 5%-40% (vol/vol) followed by another 10-min
gradient of 40%-95% (vol/vol) acetonitrile contain-
ing 0.1% formic acid/O.Ol% trifluoroacetic acid at a
rate of 0.2 pL/min. The QSTAR mass spectrometer
was set to iteratively acquire a positive time-of-flight
(TOF) MS scan at 1-s accumulation time between 400
and 1,700 mlz followed by MS/MS scans at 5-s accu-
mulation time between 50 and 2,500 m/z of the three
most abundant ions from the preceding MS scan. Un-
processed data files containing MS/MS spectra from
the QSTAR instrument were submitted to the Mascot
search engine (Matrix Science Ltd., London, UK) for
database searching and protein identification using
the Mascot Daemon application (32). The SwissProt-
Trmbl database and the National Center for Biotech-
nology Information (NCBI) nonredundant database
were searched using Homo sapiens as a taxonomic re-
Geno. Prot. Bioinfo.
RT-PCR w a s carried out on extracted total RNA as
described previously (3). Total RNA from cells was
extracted using TRI Reagent@ (Molecular Research
Center, Inc., Cincinnati, USA). 2 pg of total RNA
was reverse transcribed with oligo (dT) and murine
leukemia virus (MuLV) reverse transcriptase accord-
ing to the protocol supplied with the GeneAmp RNA
PCR Core Kit (PE Applied Biosystems) and am-
plified using Tag polymerase. PCR [28 cycles; melt-
ing temperature (Tm)= 58”CI was performed with
the GMFG and glyceraldehyde 3-phosphate dehydro-
genase (GAPDH) primers. GMFG: forward primer
= 5’-AAAGAAGAGGCCTGTGGACAG-3’, reverse
primer = 5’-TGGTTGTTCAGGTCCTAGGG-3’;
GADPH: forward primer = 5’-GTATCGTGGAAGA
ACTCATGAC-3’, reverse primer = 5’-TGCCAGT
GAGCTTCCCGTCAGC-3’. The PCR product size
for each gene was determined and matched the ex-
Bioinformatic analysis for GMFG tissue
High-throughput gene expression profiling has be-
come an important tool for investigating transcrip-
tional activity of the human GMFG gene in a va-
riety of biological samples. We gathered all pub-
lished microarray gene expression datasets in which
the GMFG gene was expressed. We used Su’s dataset
(http://expression.gnf.org/) as a key base, in which
gene expression is profiled from 91 human and mouse
samples across a diverse array of tissues, organs,
and cell lines; 101 unique specimens representing
47 tissue/cell lines are represented. We carried out
an integrated bioinformatic analysis on GMFG us-
ing Perou’s dataset on responses of human mam-
mary epithelial cells to EGF, TGF-beta 1, interferon,
and growth on Matrigel; Mm’s dataset (4) on hu-
man CD34+ hematopoietic stem/progenitor cells; and
Zhang’s dataset (18) on human CD34+ hematopoietic
stem/ progeni t or cells.
Bioinformatic analysis for the promoter
of the GMFG gene
We used two computational prediction tools to search
for TF binding sites: the TFSEARCH program (33),
which employs the Position Weight Matrix method,
and our GeneKey software (34), which uses a novel
Vol. 4 No. 3 2006 153
GMFG and Hematopoiesis
Shuffled Matrix method. By averaging the two scores
obtained from TFSEARCH and GeneKey, we defined
a new score, ranging from 0.0 to 100.0, with a higher
score indicating a higher probability of a putative TF
binding site. The 5'-flanking 750-bp promoter region
of the GMFG gene was analyzed.
Bioinformatic analysis for
To better understand the molecular evolution of
GMFG, we collected the GMFG gene sequences
from multiple species using our GeneKey software
(34) on data from the NCBI UniGene and ex-
pressed sequence tag (EST) databases, NCBI Human
Genome Resources (http://www.ncbi.nlm.nih.gov/
genome/guide/human/) , Ensembl Genome Browser
Genome Browser (http://genome.ucsc.edu/cgi-bin/
hgGateway). GeneKey software was designed to as-
semble ESTs to cDNA/mRNA sequences and trans-
late the mRNA to corresponding protein sequences.
To establish a phylogenetic tree for GMFG, our Ma-
ligner software (35) was used. Another software pro-
gram, Sandwich Sequence Alignment, was created
and used to evaluate the similarities of the third se-
quence to two, instead of one, family members.
and UCSC Human
We thank Drs. Rafael Daniel Camerini-Otero and
Peggy Hsieh for providing 2D image equipment and
2D analysis software, Dr. Chu-Xia Deng for sharing
2D analysis software, and Dr. Heidi Hoffman for as-
sisting with protein identification.
YS carried out proteomics experiments and drafted
the manuscript. LC carried out the cell cultures and
PCR experiments. LAL participated in the 2D data
analysis and helped to draft the manuscript. HHW
performed the bioinformatics study. GPR coordi-
nated the study, participated in its design, and helped
to draft the manuscript. All authors read and aP-
proved the final manuscript.
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