TRANSCRIPTIONAL PROFILING OF HUMAN AMNIOTIC FLUID-DERIVED STEM
CELLS - WHERE DO THEY RESIDE IN THE DEVELOPMENTAL CONTINUUM?
David Mack1, Kathryn Gallaher1 and Stephen J Walker1
1Wake Forest Institute for Regenerative Medicine, Winston-Salem, NC, USA
Introduction
Results
Functional Annotation
Because of their fetal origin, it has been postulated that
amniotic fluid-derived stem (AFS) cells lie phenotypically
somewhere between embryonic (ES) and adult somatic stem
cells. The expression of approximately 90 "stem cell-related"
genes was recently measured in 22 clones of hAFS cells and
compared to hES/iPS cells and adult bone marrow-derived
mesenchymal stromal cells (MSCs). The analysis of the
expression of this limited number of genes appears to
corroborate that while AFS cells express a battery of MSC-like
cell surface markers, they also share at least a partial gene
expression profile of more pluripotent ES cells (like the
expression of SSEA-4). Therefore, our goal was to take this
analysis a step further by employing whole-genome microarray
profiling to more fully characterize gene expression in these
three cell types.
Methods
Total RNA was extracted from two human ES cell lines (H7 and
H9), two BM-MSC lines (commercially available from Lonza and
PromoCell) and two AFS cell lines isolated in house (A1 and
H1). The quantity and purity of the extracted RNA was
evaluated using a NanoDrop ND-1000 spectrophotometer
(Nanodrop Technologies, Wilmington, DE) and its integrity
measured using an Agilent Bioanalyzer. For microarray
hybridizations, 1.5 ug of amplified cDNA from each sample was
labeled with Arrayit 540 dye (Arrayit; Sunnyvale, CA) using the
Arrayit Aminoallyl cDNA Labeling kit (Arrayit; Sunnyvale, CA)
following the manufacturer’s protocol. The amount and quality
of the fluorescently labeled cRNA was assessed using a
NanoDrop (ND-1000) spectrophotometer and an Agilent
Bioanalyzer. Following manufacturer’s specifications, 2.0 ug of
540-labeled cRNA was hybridized to Human H25K WholeGenome Microarrays (Arrayit; Sunyvale, CA) for 3.5 hrs, prior
to washing and scanning. Data were extracted from scanned
images using Arrayit’s Feature Extraction Software .
Background subtracted intensity data were generated for each
transcript within each of the six samples. Following removal of
transcripts for which the annotation was incomplete, there
were ~16,000 data points for each sample. These were rankordered based on intensity, (from 1 to 65,000) and transcripts
displaying an intensity of 200 or greater (background + 2SD)
were used for further analysis. All genes displaying an
intensity value of >200 were then evaluated in a Venn diagram
to display genes that were: (a) expressed in all three cell types,
(b) expressed exclusively in a single cell type or (c) expressed
in two of the cell types but not the third.
KEGG Pathways
Common to ES and AFS Cells (648 expressed transcripts)
Term
Count
%
Phosphoprotein
418
66.9
Nucleus
304
48.6
Mitotic Cell Cycle
72
11.5
Cell Cycle Phase
80
12.8
Cell Cycle
107
17.1
Organelle Fission
55
8.8
Intracellular Non-Membrane-Bounded Organelle
184
29.4
Chromosome
71
11.4
Nuclear Lumen
126
20.2
Intracellular Organelle Lumen
138
22.1
P-Value
6.4E-53
1.4E-50
6.6E-35
7.9E-35
2.6E-33
1.1E-28
1.3E-28
3.8E-28
7.1E-26
8.4E-24
Common to ES and AFS Cells
Term
Count
Cell Cycle
20
DNA Replication
9
Pyrimidine Metabolism
11
Homologous Recombination
6
Oocyte Meiosis
11
Pathways in Cancer
20
Small Cell Lung Cancer
8
Spliceosome
10
Mismatch Repair
4
RNA Degradation
6
Non-Homologous End-Joining
3
Prostate Cancer
7
Ubiquitin Mediated Proteolysis
9
%
3.2
1.4
1.8
1.0
1.8
3.2
1.3
1.6
0.6
1.0
0.5
1.1
1.4
P-Value
2.8E-8
2.0E-5
1.3E-3
2.2E-3
4.0E-3
1.5E-2
2.3E-2
2.7E-2
4.2E-2
4.3E-2
7.0E-2
8.1E-2
9.4E-2
D
Functional Annotation
Unsupervised principle component analysis revealed that the ES
cell lines and the AFS cell lines cluster reasonably close together,
whereas the MSC lines display a somewhat higher degree of
variation. This result makes sense given that both the ES and AFS
cell lines are clonal populations but the commercially available
MSCs are mixed populations isolated solely on their adherence to
plastic.
KEGG Pathways
Common to MSC and AFS Cells (890 expressed transcripts)
Term
Count
%
Golgi Apparatus
80
9.2
Vesicle-Mediated Transport
64
7.4
Skeletal System Development
44
5.1
Phosphoprotein
405
46.6
Blood Vessel Development
35
4
Endoplasmic Reticulum
86
9.9
Negative Regulation of Phosphorylation
14
1.6
P-Value
8.3E-8
1.3E-6
8.2E-7
2.2E-7
5.4E-5
9.1E-5
5.7E-5
Regulation of I-kappaB Kinase/NF-kappaB Cascade
Negative Regulation of Phosphate Metabolic Process
Regulation of Protein Kinase Cascade
Focal Adhesion
Regulation of Cell Growth
Positive Regulation of Signal Transduction
Cell Motion
Identical Protein Binding
5.7E-5
9.4E-5
1.2E-5
5.9E-5
1.6E-4
1.6E-4
1.5E-4
9.1E-4
20
14
32
29
28
36
49
58
2.3
1.6
3.7
3.3
3.2
4.1
5.6
6.7
Common to MSC and AFS Cells
Term
Count
Focal Adhesion
29
MAPK Signaling Pathway
29
ECM-Receptor Interaction
13
Apoptosis
13
Lysosome
15
Wnt Signaling Pathway
17
Endocytosis
19
RIG-I-like Receptor Signaling Pathway
10
Cytosolic DNA-Sensing Pathway
8
Regulation of Actin Cytoskeleton
19
Axon Guidance
13
TGF-beta Signaling Pathway
10
Pathways in Cancer
25
Adherens Junction
9
p53 Signaling Pathway
8
%
3.3
3.3
1.5
1.5
1.7
2.0
2.2
1.2
0.9
2.2
1.5
1.2
2.9
1.0
0.9
P-Value
5.9E-5
7.3E-3
3.6E-2
3.7E-2
4.8E-2
6.8E-2
7.8E-2
1.3E-1
2.2E-1
2.2E-1
2.6E-1
2.6E-1
2.8E-1
2.9E-1
3.6E-1
Calcium Signaling Pathway
GnRH Signaling Pathway
Melanogenesis
Cytokine-Cytokine Receptor Interaction
1.7
1.2
1.2
2.2
3.6E-1
3.5E-1
3.3E-1
4.6E-1
15
10
10
19
Using data from the Venn diagram, the list of (890) genes that were
expressed exclusively in MSCs and AFS cells was imported into
Ingenutiy (IPA) software. Here we performed gene ontology and
pathway analysis to assess the signaling and metabolic pathways,
molecular networks, and biological processes that are most
significantly represented in a both MSCs and AFS, but not ES,
cells. The same analysis was then performed using the list of
genes (648) common and exclusive to AFS and ES cells. The gene
ontology (functional annotation) for each comparison is displayed
in the tables on the left, and the pathway analysis results are in the
tables to the right.
Conclusions
A Venn diagram generated from a comparison of ~7000 of the most
highly expressed genes from each cell type (ES vs. AFS vs. MSC)
showed that 65% of the transcripts are expressed in all three. AFS
cells and MSCs shared an additional 890 expressed transcripts,
bringing their transcriptional similarity up to approximately 78%.
The original hypothesis that AFS cells are more similar to ES cells
than are MSCs was supported by these data. AFS and ES cells
share an additional 648 common transcripts whereas MSCs and
ES cells only share an additional 70 transcripts.
The gene expression data generated in this study suggest that:
(1) gene expression between individual MSC cell lines is more
variable than gene expression in either AFS or ES cell lines and,
(2) AFS cells share more common transcript expression with ES
cells than do MSCs.
Future Directions
RNA and DNA derived from the six cells lines assayed in this pilot
study will be used to take the characterization further. Through
microRNA and epigenetic (promoter methylation) profiling we
should better able to describe molecular features that define
functional aspects of each of these three cell types.
Wake Forest Institute for REGENERATIVE MEDICINE