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doi:10.1016/j.bi

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Biomaterials 27 (2006) 5978–5989

www.elsevier.com/locate/biomaterials

Effect of 3D scaffold and dynamic culture condition on the global geneexpression profile of mouse embryonic stem cells

Hui Liua,1,2, Jian Linb,2, Krishnendu Royc,�

aDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USAbDepartment of Molecular Genetics and Microbiology, The University of Texas at Austin, Austin, TX 78712, USA

cThe Institute of Cellular and Molecular Biology, The University of Texas at Austin, Austin, TX 78712, USA

Received 27 March 2006; accepted 19 May 2006

Available online 7 July 2006

Abstract

We have previously demonstrated that mouse embryonic stem (ES) cells differentiated on three-dimensional (3D), highly porous,

tantalum-based scaffolds (CytomatrixTM) have significantly higher hematopoietic differentiation efficiency than those cultured under

conventional two-dimensional (2D) tissue culture conditions. In addition, ES cell-seeded scaffolds cultured inside spinner bioreactors

showed further enhancement in hematopoiesis compared to static conditions. In the present study, we evaluated how these various

biomaterial-based culture conditions, e.g. 2D vs. 3D scaffolds and static vs. dynamic, influence the global gene expression profile of

differentiated ES cells. We report that compared to 2D tissue culture plates, cells differentiated on porous, CytomatrixTM scaffolds

possess significantly higher expression levels of extracellular matrix (ECM)-related genes, as well as genes that regulate cell growth,

proliferation and differentiation. In addition, these differences in gene expression were more pronounced in 3D dynamic culture

compared to 3D static culture. We report specific genes that are either uniquely expressed under each condition or are quantitatively

regulated, i.e. over expressed or inhibited by a specific culture environment. We conclude that that biomaterial-based 3D cultures,

especially under dynamic conditions, might favor efficient hematopoietic differentiation of ES cells by stimulating increased expression of

specific ECM proteins, growth factors and cell adhesion related genes while significantly down-regulating genes that act to inhibit

expression of these molecules.

r 2006 Elsevier Ltd. All rights reserved.

Keywords: Embryonic stem cells; Differentiation; Spinner culture; Gene expression; cDNA microarray

1. Introduction

The fate of stem cells is regulated by both intrinsic andextrinsic signals. While intrinsic regulators mainly includetranscription factors and factors controlling cell division,maintenance and lineage specific differentiation of stemcells ultimately depends on cell autonomous regulatorsmodulated by external signals in the niche, which includessoluble factors, cell–cell interactions mediated by integralmembrane proteins and interactions between cell-surface

e front matter r 2006 Elsevier Ltd. All rights reserved.

omaterials.2006.05.053

ing author. Tel.: +1512 232 3477; fax: +1 512 471 0616.

ess: kroy@mail.utexas.edu (K. Roy).

Zimmer Inc., Austin, TX, USA.

rs contributed equally to this work.

molecules and the extracellular matrix (ECM) [1]. For stemcells cultured within synthetic, biomaterial-based scaffoldenvironment these interactions are manifested through co-culture conditions, cell seeding density and scaffoldarchitecture as well as through the mechanical and surfaceproperties of the scaffold substrate. Of much interest is thecorrelation between these extrinsic, microenvironmentalsignals and corresponding changes in gene expression thatleads to either long-term maintenance or lineage specificdifferentiation of stem cells.In the past several years, a number of studies, devoted to

identifying the global gene expression profiles of stem cells,have specified genes that might play important roles inmaintaining the ‘‘stemness’’ of stem cells [2–4], genes thatare uniquely expressed during differentiation [5–7] and

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genes that determine specific differentiation pathways[8–11]. Since signals from the stem cell microenvironmentmust play a crucial role in cell fate determination, asignificant number of studies have been focusing onidentifying the molecular signals elaborated in thestem cell niche [12–16]. Recent advances in cellularand tissue engineering have led to a focused efforton culturing and differentiating embryonic stem (ES) cellsin a variety of biomaterials and three-dimensional (3D)scaffold structures as well as under various cultureconditions [17–23]. Although phenotypic changes of EScells cultured in these environments have been character-ized, studies exploring how specific biomaterials andvarious culture conditions lead to differences in geneexpression profiles have been limited. We have recentlydemonstrated [17] that compared to traditional two-dimensional (2D) culture conditions, highly porous 3Dtantalum-based scaffolds (CytomatrixTM) and dynamicculture conditions provide a more conducive microenvir-onment for hematopoietic differentiation of mouse EScells. Cells differentiated in these CytomatrixTM scaffoldsdemonstrated unique characteristics, including less aggre-gation of embryoid bodies (EBs) and an ECM-likemembrane structure covering the EBs and extending tothe scaffold surface. ES cells cultured on these scaffoldsalso demonstrated higher hematopoietic differentiationefficiency compared to 2D culture, with a 2-fold enhance-ment in dynamic culture and 1.5-fold enhancement in staticculture [17].

In the present study, we investigated how CytomatrixTM

scaffolds and the various culture conditions influencethe global gene expression profile of mouse ES cellsusing cDNA microarray analysis. DNA microarrayshave become a routine tool to assess gene expressionin cells and tissues. Recently, microarray analysis has beendemonstrated to provide an integrated view of cell–biomaterial interactions [24–30]. Our ultimate goalis to identify the genetic and molecular changesthat underlie the phenotypic differences observed between2D and scaffold-based culture as well as static anddynamic culture of ES cells. The results presentedhere demonstrate that compared to differentiationin 2D tissue culture plates, ES cells differentiated on 3DCytomatrixTM scaffolds, especially under dynamiccondition, possessed significantly higher expressionlevels of key genes that function in ECM production,growth factor and cytokine activity, as well as incell growth and differentiation regulation. It is also evidentthat the dynamic culture condition further enhancesdifferentiation by significantly down-regulating a largenumber of genes that works to inhibit the expressionof the above-mentioned molecules. We conclude thatthese specific changes in gene expression profile mightplay an important role in the observed beneficial effectsof biomaterial-based 3D culture during ES cell hemato-poiesis and therefore warrants further, more directedinvestigation.

2. Materials and methods

2.1. Scaffolds and dynamic culture environment

The CytomatrixTM scaffold (Cytomatrix, Woburn, MA) and the

dynamic culture apparatus (SW Spinner flask, Cytomatrix, Woburn,

MA) used in this study have been previously reported [17]. Briefly,

CytomatrixTM is a highly porous and cell-compatible device made of

tantalum. The average pore size, as specified by the manufacturer, is

o150mm. In a recent study, these scaffolds were shown to enhance the

viability and maintain the multipotency of hematopoietic progenitor cells

(HPCs) in long-term culture without the need for exogenous cytokines

[31]. In addition, they have been used to successfully generate human T

cells from CD34+ progenitors in vitro by co-culturing with mouse thymic

stromal cells [32].

Spinner flask bioreactors have been successfully applied in tissue

engineering, specifically for regenerating bone tissue [33] and for cartilage

differentiation [34,35]. Recent studies have shown that increase in mass

transport in spinner flask culture enhances proliferation and differentia-

tion of marrow stromal osteoblastes seeded on porous scaffolds [36]. The

unique combination of 3D scaffold architecture and dynamic culture

could provide a highly conducive microenvironment for efficient cell

growth and differentiation.

2.2. Cell culture

R1 murine ES cells were generously provided by Dr. A. Nagy (Mount

Sinai Hospital, Ont., Canada). STO fibroblast cells that have been stably

transfected with a leukemia inhibitory factor (LIF) gene were a gift from

Ms. Shanna Maika (Animal Research Center, The University of Texas at

Austin). ES cells were cultured and differentiated in 2D, 3D-static and 3D-

spinner culture as described by us before [17]. Briefly, undifferentiated ES

cells were maintained and expanded on a layer of irradiation-inactivated

STO cells in a complete ES cell maintaining medium containing 15% ES-

CultTM fetal bovine serum (Stem Cell Technologies, Vancouver, Canada),

2mM Glutamine, 100U/mL penicillin G and 10 mg/mL streptomycin,

0.1mM non-essential Amino acids and 5� 10�5 M 2-mercaptoethanol in

Iscove’s modified Dulbecco’s medium (IMDM) (Gibco-Invitrogen, Rock-

ville, MD). Cells were pre-differentiated for 48 h by feeder-free culture on

gelatinized tissue culture plates in complete ES maintaining medium,

supplemented with 1000U/mL of recombinant LIF (Chemicon, Temecula,

CA), followed by LIF withdrawal to encourage EB formation. At this

stage, single ES cells were either plated onto bacteriological plastic plates

at 4� 105 cells per 90mm plate (2D) or seeded onto CytomatrixTM

scaffolds (Cytomatrix, Woburn, MA) at 2� 105 cells per 9mm diameter

unit. ES cell seeding was achieved by drop-wise addition of cell suspension

to each individual scaffold. The cell-seeded CytomatrixTM scaffolds were

incubated for 4 h in a humidified incubator to allow cell attachment,

followed by either transfer into six-well plates (3D-static) or assembly into

the CytomatrixTM SW-spinner system (Cytomatrix) according to manu-

facturer’s protocol (3D-spinner). The SW-spinner systems were placed on

a CellgroTM magnetic stirrer (Barnstead International, Bubuque, IA) and

cultured under low stirring speed. Medium was changed every 2 days for

each system.

2.3. RNA isolation

Total RNA was isolated either from undifferentiated ES cells (as

control) or from ES cells differentiated for 14 days under 2D or 3D culture

conditions (three independent biological repeats for each culture condi-

tions). RNA extraction was performed using Trizol reagent according to

manufacturer’s protocol (Gibco-Invitrogen). The cell/CytomatrixTM

complexes from 3D-static and 3D-spinner culture were collected into

50ml centrifuge tubes and washed 3� with Dulbecco’s phosphate

buffered saline (D-PBS) (Gibco-Invitrogen). Identical washes were also

performed with cells differentiated in 2D culture as well as undiffer-

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Fig. 1. Venn diagram of differentially expressed genes in ES cells culture

under 2D and 3D conditions. Features that were only detected in one or

two culture conditions but not in others were considered as uniquely

detected genes. Features that were detected in all three culture conditions

were considered as commonly detected genes. 3DSP ¼ 3D spinner culture;

3DST ¼ 3D static culture.

H. Liu et al. / Biomaterials 27 (2006) 5978–59895980

entiated R1 ES cells. Quality of the total RNA was assessed using

NanoDrops ND-1000 UV-Vis Spectrophotometer (NanoDrop Technol-

ogies, Wilmington, DE) and gel electrophoresis. Only those RNA with a

2:1 ratio of ribosomal bands and an A260/A280 ratio of 1.9–2.1 were used

for cDNA array hybridization.

2.4. cDNA labeling, hybridization and array scanning

Total RNA samples were labeled with 3DNA Array 350 Expression

Array Detection Kit (Genisphere, Hatfield, PA) according to manufac-

turer’s protocol. Briefly, 5mg of total RNA was mixed with reverse

transcription primers tagged with specific 3DNA capture sequence,

1 pmole Cy3 for test samples or 1 pmole Cy5 for hybridization references

and brought to 10 mL with nuclease free water followed by incubation for

10min at 80 1C. After cooling down on ice for 3min, an equal volume of

reaction mixture: 4mL 5� SuperScript II First Strand Buffer, 20mM

DTT, 200U SuperScript II reverse transcriptase (Gibco-Invitrogen), 1mLdNTP mix (10mM each for dATP, dCTP, dGTP, dTTP) and 1mLSuperase-In were added to each reaction followed by incubation at 42 1C

for 2 h. The reactions were terminated by adding 0.074 N NaOH and

7.4mM EDTA with incubation at 65 1C for 10min followed by

neutralization using 0.175M Tris-Cl, pH 7.5. The Cy3 and Cy5 reactions

were then combined and the generated cDNA was concentrated using

Millipore Microcon YM-30 Centrifugal Filter Devices (Millipore, Bill-

erica, MA) according to manufacturer’s protocol.

Array hybridization was performed using a cDNA array fabricated by

Prof. Vishwanath Iyer’s laboratory at The University of Texas at Austin.

This particular array contains 36,880 mouse clones from National

Institutes of Aging (NIA). The NIA sets, specifically the NIA 15K array

has been used by Tanaka et al. [37] to analyze and study R1 ES cells and

their gene expression patterns. In addition, the database of new NIA

cDNA set and the related analysis tools are available as open source

material from Dr. Iyer’s lab (http://chipmunk.icmb.utexas.edu/ilcrc/lt/

clones_search.htm). To perform array hybridization, we followed the

successive hybridization protocol from Genisphere (Hatfield, PA). Briefly,

10mL concentrated cDNA, 25 mL 2� formamide-based hybridization

buffer (pre-warmed to 55 1C), 2mL LNA dT Blocker and 13 mL nuclease

free water were incubated at 75 1C for 10min followed by loading between

a post-processed microarray slide and a LifterslipTM (Erie Scientific,

Portsmouth, NH). The hybridizations were carried out in a humidified

chamber at 50 1C for 16 h. The arrays were washed and used for

subsequent 3DNA hybridization: 25 mL 2� formamide-based hybridiza-

tion buffer, 2.5 mL Cy3 capture reagent, 2.5 mL Cy5 capture reagent, and

20mL nuclease free water were mixed and incubated at 75 1C for 10min

followed by loading between a washed array slide and a LifterslipTM (Erie

Scientific). Hybridizations were carried out in a humidified chamber in the

dark at 50 1C for 3 h. Hybridized arrays were washed and slides were dried

under centrifugation at room temperature. Dried slides were scanned with

an Axon Genepix 4000 scanner (Axon, Union City, CA). Images were

subsequently analyzed using Axon Genepix 5.0 software. Three biological

repeats were performed for each experimental condition.

2.5. Data analysis and statistics

The default feature detection parameters of Genepix 5.0 were used for

spot detection. The arrays were normalized in the Longhorn Array

Database (LAD), developed at the University of Texas at Austin [38].

Normalization was based on the assumption that the log-transformed

ratio of net red (Cy5) channel intensity to net green (Cy3) channel

intensity for each spot was centered on zero. The normalized ratio of

medians was the raw ratio of medians divided by the calculated

normalization factor. Spots with signal-to-noise ratios below 2 were

flagged. Genes that were not flagged in at least two out of three biological

repeats were used for further analysis. The ratio of the red (sample) to

green (reference) channels for each spot was expressed as log2(R/G) as

reported previously [39]. These log2-transformed data were used for

further analysis. Missing values were estimated by a K Nearest Neighbor

(KNN) analysis widely used for microarray data [40]. Hierarchical

clustering was performed and displayed using Cluster 3.0 and Java

TreeViewTM software. GO annotations were assigned to arrayed genes

using DAVID http://david.niaid.nih.gov/david/. One-way ANOVA was

performed to obtain the gene-specific p-values for determination of

significance levels among the three different culture conditions. In

addition, genes whose median expression ratio in one culture condition

differed from that in another culture condition by at least two folds (i.e.

log2 ratio X1 or p�1) were obtained. An ANOVA p-value of o0.05,

along with this X2 folds change in expression level, enabled us to identify

genes that exhibited substantial changes.

3. Results

The arrays used in this study consisted of 36,880 clones,which represented 25,158 distinct genes. The averagenumber of features detected in each culture conditionranged from 14,273 to 15,223 per array. In order to studythe differential gene expression between 3D and 2D cultureas well as dynamic versus static culture [41], we focused ourefforts on analysis of genes that demonstrated differentexpression patterns between the culture conditions. Speci-fically, we identified two types of differentially expressedgenes: (a) uniquely expressed genes i.e. genes that areexclusively expressed in one or two types of culture but notall three culture conditions and (b) quantitatively differentgenes i.e. genes that are expressed under all culture typesbut were either up-regulated (i.e. over expressed) or down-regulated (i.e. inhibited) between the various conditions.

3.1. Uniquely expressed genes identified in 2D and 3D

culture

Fig. 1 shows a Venn diagram indicating the number ofclones that were exclusively detected under each culture

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Table 1

Partial list of uniquely expressed genes

2D

Transcription

Mm.162811 RAB8A, member RAS oncogene family

Mm.131150 DEK oncogene (DNA binding)

Mm.1011 Nuclear receptor coactivator 3

Mm.4269 Transcription factor 4

Mm.15755 Transcriptional regulator, SIN3A (yeast)

Proliferation

Mm.31927 Transmembrane 4 superfamily member 9

Differentiation

Mm.274432 Protein phosphatase 3, catalytic subunit, beta

isoform

Cell death

Mm.24103 Death associated protein kinase 1

3D-static

Transcription

Mm.3798 Fumarylacetoacetate hydrolase

Mm.235580 Retinoblastoma-like 2

Mm.913 Brachyury

Mm.6743 Nuclear factor, erythroid derived 2,-like 1

Mm.4618 Trans-acting transcription factor 1

Cell growth

Mm.235580 Retinoblastoma-like 2

Mm.105585 Progressive external ophthalmoplegia 1

(human)

Mm.37341 Anaphase promoting complex subunit 7

Mm.210134 Ribosomal protein S6 kinase, polypeptide 1

Mm.132857 Transmembrane 9 superfamily member 1

Mm.4533 Apolipoprotein A-IV

Mm.25843 Tigger transposable element derived 2

3D-Spinner

ECM production

Mm.269747 Latent transforming growth factor beta

binding protein 1

Mm.275320 Elastin

Mm.7524 Dystroglycan 1

Mm.259316 synaptotagmin 11

Cell growth

Mm.12864 RIKEN cDNA 1190002L16 gene

Mm.28300 Zinc finger, DHHC domain containing 3

Mm.196110 Hemoglobin alpha, adult chain 1

Transcription

Mm.277236 Development and differentiation enhancing

Mm.262037 Eukaryotic translation initiation factor 1A

Mm.274237 Interferon regulatory factor 2 binding protein 1

Mm.148748 Myeloid/lymphoid or mixed lineage-leukemia

translocation to 1 homolog (Drosophila)

Mm.29891 Forkhead box O1

Mm.6167 Homeo box C8

Mm.21649 RIKEN cDNA 9430034D17 gene

Mm.243802 Basonuclin

Mm.273695 Interferon regulatory factor 6

Mm.22501 RIKEN cDNA 3526402J09 gene

Mm.257482 Apoptosis antagonizing transcription factor

Proliferation

Mm.46401 Son cell proliferation protein

Differentiation

Mm.198803 UDP-glucose ceramide glucosyltransferase

Mm.277236 Development and differentiation enhancing

Mm.6813 Bone morphogenetic protein 4

Table 1 (continued )

3D-static and 3D-spinner

ECM production

Mm.7281 Procollagen, type V, alpha 1

Mm.277792 Procollagen, type I, alpha 2

Transcription

Mm.275071 Jun oncogene

Mm.219675 G elongation factor, mitochondrial 2

Mm.3960 Interferon regulatory factor 3

Mm.259295 Pbx/knotted 1 homeobox

Mm.270511 Transcription elongation regulator 1 (CA150)

Mm.279103 SRY-box containing gene 17

Cell growth

Mm.51136 Casein kinase II, alpha 2, polypeptide

Mm.33773 NIMA (never in mitosis gene a)-related

expressed kinase 2

Mm.3991 Solute carrier family 25 (mitochondrial carrier;

dicarboxylate transporter), member 10

Mm.2551 SEC22 vesicle trafficking protein-like 1 (S.

cerevisiae)

Differentiation

Mm.41925 Meteorin, glial cell differentiation regulator

H. Liu et al. / Biomaterials 27 (2006) 5978–5989 5981

condition along with the number of clones that weredetected in both 3D culture (static and dynamic) but notunder 2D conditions. As shown, 1852 unique clones weredetected only under 2D culture, 938 clones only under 3Dstatic, 1722 clones detected only in 3D dynamic culture and718 unique clones were detected only in the 3D cultures(both static and dynamic) but not in 2D. These differen-tially expressed clones were uploaded into DAVID andclassified into groups based on their biological functions.These functional groups primarily fell into seven majorcategories including binding, catalytic activity, cell com-munication, cellular physiological process, intracellular,membrane, and metabolism (data not shown). To elucidatehow the different culture conditions affect ES cell behaviorand differentiation, we analyzed the expression profile ofseveral key genes from this categorized database.Table 1 is a partial list of genes that are either uniquely

expressed in one of 2D, 3D-static or 3D-spinner culture orare expressed in both 3D culture but not in 2D. These genesinclude those that regulate ECM production, transcriptionactivity, cell proliferation, differentiation and apoptosisand might play important role in ES cell maintenance anddifferentiation. Comparison of these genes (Table 1)reveals some interesting results:

(a)

Genes involved in ECM production, including elastin,latent transforming growth factor beta binding protein1 and dystroglycan 1 were only expressed in 3D-spinnerculture while two procollagen genes were expressed inboth 3D culture but not in 2D culture.

(b)

A large number of genes involved in transcriptionactivities were uniquely detected in both 3D cultures.For example, interferon regulatory factor 6, myeloid/

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lymphoid or mixed lineage-leukemia translocation to 1homolog and forkhead box O1 were only expressed inES cells cultured in 3D-spinner conditions while trans-acting transcription factor 1, retinoblastoma-like 2 andbrachyury were expressed in 3D-static culture. Further,interferon regulatory factor 3 and transcription elonga-tion regulator 1 (CA150) were detected in both 3Dculture, but not under 2D condition. In the contrary,two transcriptional co-repressor genes: transcriptionfactor 4 and transcriptional regulator SIN3A weredetected in 2D culture and were shut down under 3Dconditions.

(c)

Several key regulatory genes were also expressed onlyin 3D culture. For example, the cell growth regulatorygenes, retinoblastoma-like-2 and anaphase promotingcomplex subunit 7 were both detected in 3D-staticculture and the cell proliferation-differentiation controlgenes, son cell proliferation protein, forkhead box O1and bone morphogenetic protein 4 (BMP4) wereexclusively detected in 3D-spinner culture.

(d)

Furthermore, death associated protein kinase 1, a geneencoding DAP-kinase that is involved in the inductionof early apoptotic pathways [42], was uniquely ex-pressed in 2D culture but not under any 3D conditionsindicating that 3D conditions might prevent apoptoticdeath of stem cells during culture.

3.2. Quantitatively different genes identified in 2D and 3D

culture

In addition to the features that were uniquely detected ineach culture, 7784 clones which represented 4981 uniquegenes were measured as quantitatively different betweenthe three cultures, i.e. they were expressed under all cultureconditions (Fig. 1) but significantly up or down-regulatedin specific culture conditions. Among these, 948 genes weredetermined to have statistically significant differentialexpression (po0:05 by ANOVA analysis across all threeconditions, n ¼ 9 and at least 2-fold change as detailed inSection 2).

As shown in Fig. 2A, among the three culture condi-tions, ES cells cultured in 3D-spinner culture exhibited thelargest number of statistically significant, differentiallyexpressed genes, both up-regulated (2.23 times that of 2Dculture and 1.85 times that of 3D-Static culture) and down-regulated (7.59 times that of 2D and 4.51 times that of 3D-Static). In addition, although similar number of genes wereup-regulated in 2D and 3D-static culture, a significantlylarger number of genes (1.66 times that of 2D) weredown-regulated in cells cultured under 3D-static conditions(Fig. 2A).

Fig. 2B shows the number of genes exhibiting statisti-cally significant (po0:05 by one way ANOVA) differentialexpression between each pair of culture conditions. Thisdata represents a direct comparison of gene expressionbetween the experimental groups and helps to elucidate the

relative influence of 3D structure and dynamic cultureconditions. As shown, the number of genes exhibitingsignificantly different expression profile varies as: 2D vs.3D-spinner43D-static vs. 3D-spinner43D-static vs. 2D,suggesting that dynamic culture conditions might havesignificantly larger effect on ES cell gene expression anddifferentiation compared to scaffold structures alone.The biological functions of these quantitatively different

genes (over expressed or inhibited) were further analyzedby functional grouping through DAVID. The functionalgroups identified, fell primarily into nine major categoriesincluding binding, catalytic activity, cell communication,cellular physiological process, intracellular, metabolism,membrane, response to stimulus and transporter activity(data not shown). These categorized genes were furtheranalyzed to identify the key differences in over expressionand inhibition pattern of genes during 3D and 2D cultureof ES cells. Fig. 3 provides a comparison of expressionlevels of selected genes involved in (A) ECM production,(B) growth factor secretion (C) cell adhesion and (D) celldifferentiation. Genes that exhibited maximum changes inexpression are shown. A positive value indicates overexpression while a negative value in the bar graph indicatesdown-regulation (inhibition) of the specific gene. The dataindicates several key features:

(a)

Among the ECM-related genes, three pro-collagengenes were significantly up-regulated in both 3Dcultures with highest expression in 3D dynamic culture.Moreover, matrix metalloproteinase 15, a key ECMdegradation enzyme [43,44], was down-regulated inboth 3D culture with lowest expression in 3D dynamicculture while tissue inhibitor of metalloproteinase 1, akey molecule involved in increased ECM production[45,46] was significantly less down-regulated in both 3Dculture with highest expression in 3D dynamic culture(Fig. 3A).

(b)

Several growth factors/cytokines and their activityregulator genes were found to be significantly up-regulated in 3D-spinner culture. This include insulin-like growth factor 2, insulin-like growth factor bindingprotein 4 and insulin-like growth factor 2 bindingprotein 3, while one insulin-like growth factor andinsulin-like growth factor (IGF) receptor were down-regulated (Fig. 3B).

(c)

Evaluation of cell adhesion and cell differentiationrelated genes indicate several key genes that aredifferentially expressed (up or down-regulated in 3Dculture with largest change in 3D dynamic culture).Fig. 3C indicates that several of these genes areinhibited during ES cell differentiation in 3D culturewith highest expression in 2D culture and progressivelylower expression in 3D static and 3D dynamic culture.As shown in Fig. 3D Lgals1 and Csrp2 are overexpressed under 3D conditions and dynamic culturewhile Pbx and Hps genes are significantly inhibited.

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Fig. 2. Comparison of quantitatively different genes in each culture conditions. (A) Total number of genes that are differentially expressed (up or down

regulated) in each culture condition. Only statistically significant differences (p-value o0.05 by ANOVA and X2 folds change in expression level) are

included. (B) Direct comparison of the number of genes that are significantly different between each pair of culture conditions. The differences in gene

expression in each two of the three different culture conditions were evaluated by one-way ANOVA.

H. Liu et al. / Biomaterials 27 (2006) 5978–5989 5983

Furthermore, several transcription factor genes were alsoup-regulated in 3D-spinner culture, including notch genehomolog 3, transcription factor E2a, upstream transcriptionfactor 1 and YY1 transcription factor (data not shown).

In addition to these functionally grouped genes we alsoidentified specific genes that were maximally affected byeach of these culture environments. Table 2 shows the listof genes that exhibited more than 5� increased expression(po0:05 by ANOVA) in 3D spinner culture compared to2D conditions. Similarly, Table 3 provides a list of up-regulated genes (at least 2 folds over expression in 3D-spinner culture) that are statistically most significant(po0:0005). This data provide a comprehensive list ofgenes, along with their annotated description, that under-went the most significant changes in expression profileduring ES cell culture and might help in identifying

important pathways that are critically affected by theculture environment.

4. Discussion

We have previously demonstrated that significantlydifferent differentiation efficiencies are achieved when EScells are cultured under various 2D or 3D cultureconditions [17]. Compared to traditional 2D tissueculture plates, tantalum scaffold-based 3D-static and3D-spinner culture both enhanced hematopoieticdifferentiation efficiency of ES cells (1.5- and 2-folds,respectively). In this study, we attempted to identify thegenetic-level effects of tantalum scaffolds and dynamicculture conditions on ES cell differentiation throughcDNA microarray analysis. We focused our efforts on

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identification of genes that were uniquely and differentiallyexpressed in cells cultured under each condition. Analysisof these genes indicated that as a response to these specificculture environments, ES cells altered their gene expressioneither by turning the gene on/off or by regulating theirexpression level.

4.1. Uniquely expressed genes

The comparison of genes that were only detected in cellscultured under specific conditions indicated that a sig-nificantly greater number of genes functioning in ECMproduction, growth factor/cytokine and their activityregulation, transcription activity as well as cell growthand differentiation regulation were expressed either only inthe 3D-Spinner culture or in both 3D culture, but not in 2D

Fig. 3. Expression profile of specific genes. Comparison of the expression le

production (B) cell growth (C) cell adhesion and (D) differentiation regulation

conditions. In fact, the largest number of genes involved inECM production was detected in 3D-dynamic culturefollowed by 3D-static and 2D. This might contribute to thedifferent differentiation efficiency observed in these threecultures [17] since enhanced ECM production might in turnincrease cell–cell and cell–scaffold interactions, leading toimproved cell signaling and cell differentiation.Another key uniquely expressed gene in 3D dynamic

culture is bone morphogenetic protein 4 (BMP4), which isa member of the TGF b superfamily [47–49], and a criticalgene involved in ES cell differentiation. The uniqueexpression of BMP-4 gene in 3D-spinner culture indicatesthat this could be a key pathway through which 3D-spinnerculture provides beneficial effects on ES cell differentiationcompared to 3D-static culture or 2D conditions andtherefore warrants more directed investigation.

vels (n ¼ 3) of specific genes involved in (A) extracellular matrix (ECM)

.

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Fig. 3. (Continued)

H. Liu et al. / Biomaterials 27 (2006) 5978–5989 5985

4.2. Quantitatively different gene expression

In addition to genes that were either uniquely expressedin 3D-spinner or commonly expressed in both 3D culturebut not in 2D, a considerable number of genes related tocell differentiation were differentially expressed (up- ordown-regulated) in cells cultured under specific conditions.A key observation was that a significantly larger number ofgenes were down-regulated (inhibited) in 3D-spinnercompared to 3D-static and 2D. In addition, the largestnumber of up-regulated genes was also found in 3D-spinner. Among the most significantly regulated genes(Table 3), 88.5% (54 out of 61) showed maximal change(over expression or inhibition) under 3D-spinner condi-tions. Taken together, these data suggest that dynamicculture environment has a much stronger influence on EScell gene expression compared to 3D scaffold alone.

ES cells cultured in 3D-spinner culture might enhanceECM production not only by directly increasing theexpression levels of ECM component genes, such asprocollagens, but also by down-regulating the expression

level of ECM degradation enzyme, matrix metalloprotei-nase 15 (MMP15) [47,50,51], and increasing the expression(less down-regulation compared to 2D or 3D static) oftissue inhibitor of metalloproteinase 1 (TIMP1) whichcomplexes with metalloproteinases (such as collagenases)and irreversibly inactivates them [52–55]. TIMP1, by itself,also mediates erythropoiesis in vitro, stimulating thegrowth and differentiation of human and murine erythroidprogenitors [56].Studies in a variety of species suggest that the IGF

signaling system plays a fundamental role in regulatingembryonic growth and differentiation [57]. IGFs aremitogens produced by many tissues which can stimulatecell proliferation and differentiation. Insulin-like growthfactor binding proteins (IGFBPs) have been shown toinhibit or potentiate IGF actions. They function as carrierproteins for circulating IGFs and regulate IGF turnover,transport, and tissue distribution [58,59]. They can also helpprolong the half life of IGFs in circulation from 20 to 30minfor free IGFs to over 15h for IGFs in IGF/IGFBP complex[57]. In our study, three clones of the IGF-2 gene were

ARTICLE IN PRESS

Table 2

List of genes exhibiting 45 folds difference in expression (po0:05)

Ugcluster Gene discription Fold difference p-value

Mm.31646 Actin-like 6B 52.75909661 0.005915

Mm.277792 Procollagen, type I, alpha 2 34.41563786 0.011598

Mm.268000 Vimentin 24.06508876 0.000341

Mm.20829 Epithelial membrane protein 3 20.29032258 0.000213

Mm.233799 Insulin-like growth factor binding protein 4 19.63095238 0.000138

Mm.22699 Selenoprotein P, plasma, 1 19.48066528 0.029649

Mm.7320 MAD homolog 3 (Drosophila) 17.99441786 0.000633

Mm.163 Beta-2 microglobulin 15.80025773 0.0153

Mm.43831(3) Lectin, galactose binding, soluble 1 12.83654354 0.012982

Mm.182785 Epithelial membrane protein 1 11 0.001638

Mm.17742 Transcribed locus 7.133333333 0.018869

Mm.258939 Active BCR-related gene 6.507186858 0.006855

Mm.24838 RIKEN cDNA 2810003C17 gene 6.132051282 0.027303

Mm.241601 AT rich interactive domain 4A (Rbp1 like) 5.974440895 0.007912

Mm.64542 CDNA sequence BC050188 5.8828125 0.001926

Mm.1620 Annexin A5 5.879207921 0.035344

Mm.125770 RIKEN cDNA A930027G11 gene 5.773043478 0.000395

Mm.323554 Expressed sequence AA960558 5.737373737 0.03464

Mm.277735 Procollagen, type I, alpha 1 5.715421304 0.024034

Mm.195663 Cyclin-dependent kinase inhibitor 1A (P21) 5.624126688 0.011408

Mm.2608 Biglycan 5.529411765 0.021461

Mm.100144 S100 calcium binding protein A6 (calcyclin) 5.516260163 0.027453

Mm.354403 Transcribed locus 5.464705882 0.017519

Mm.222224 WW domain-containing oxidoreductase 5.392638037 0.004028

Mm.124176 LIM motif-containing protein kinase 2 5.37037037 0.003617

Mm.286622 Peroxisomal biogenesis factor 13 5.190152801 0.042985

Mm.329353 Eukaryotic translation termination factor 1 5.145748988 0.00396

Mm.262345 Procollagen C-proteinase enhancer protein 5.120481928 0.006578

Mm.244078 Calmin 5.011695906 0.028621

Fold difference 45 and p-value o0.05.

In the order of fold difference from high to low.

Number in parentheses indicates the number of unique clones detected for that gene.

H. Liu et al. / Biomaterials 27 (2006) 5978–59895986

identified to have greatly enhanced expression in 3D-spinnerculture compared to 3D-static and 2D. IGF2 acts primarilyvia IGF1 receptor (IGF1R) [60] and IGF1R signaltransduction involves the activation of various intracellularsignaling pathways, including the Ras/Raf/MAP kinase andthe phosphoinositide-3 kinase pathways. Activation of theMAP kinase pathway subsequently leads to modifications oftranscription factors including activator protein 1(AP1) [61].Down-regulation of IGFBP1 and up-regulation of IGFBP3in both 3D cultures could regulate IGFs actions. AlthoughIGFBP4 is a potent inhibitor of IGF action in vitro [62], itsenhanced expression in 3D culture may not be significantcompared to that of IGF2.

One of the interesting cell adhesion related gene isAdam15 (named for a disintegrin and metalloprotease 15,metargidin). As shown in Fig. 3c, Adam 15 is up-regulatedin 2D culture while down-regulated in 3D, with lowestexpression in 3D spinner culture. Adam15 is a membrane-anchored glycoprotein that has been implicated in cell–cellor cell–matrix interactions and in the proteolysis ofmolecules on the cell surface or ECM [63]. In addition,Adam15 has a role in pathological neovascularization.Although there is no report about the relationship betweenAdam15 and hematopoiesis, it is conceivable that it might

affect cell differentiation through its effect on cell–matrixinteractions.In this study, we also detected a number of genes that

has been implicated in apoptotic cell death control.However, the alteration pattern of these genes in 3Dculture remains unclear as both apoptotic and anti-apoptotic genes were up-regulated. It has been reportedthat ES cell differentiation and programmed cell death aredependent upon their location within the cell aggregatesand are coordinated by the ECM [64,65].In this study we used CytomatrixTM as the scaffold

biomaterial and explored its effect on ES cell geneexpression under static and dynamic culture conditions.These scaffolds have an average pore size of o150 mm andresemble a bone like, highly porous, interconnected micro-architecture. Tantalum, as a biomaterial for tissue en-gineering scaffolds, has been shown to enhance viabilityand proliferation of hematopoietic stem cells while main-taining there multipotency [31]. They have also been usedto efficiently generate T cells in a thymic organ culturemodel [32]. It is likely that other biomaterial-basedscaffolds with similar properties would induce similarregulation of gene expression and aid in ES cell differentia-tion by up- or down-regulating genes involved in specific

ARTICLE IN PRESS

Table 3

List of genes exhibiting po0:0005 (with X2 folds difference)

Ug cluster Gene discription Fold difference p-value

Mm.233855 Eukaryotic translation initiation factor 2B, subunit 5 epsilon 2.177531207 0.000024

Mm.288602 RIKEN cDNA D230014I24 gene 3.679245283 0.000025

Mm.325827 G1 to S phase transition 1 3.060790274 0.000029

Mm.246432 Isocitrate dehydrogenase 2 (NADP+), mitochondrial 2.694292416 0.000032

Mm.260690 RIKEN cDNA 1190007F08 gene 4.263286713 0.000032

Mm.347 RIKEN cDNA 1810007M14 gene 3.773684211 0.000052

Mm.289104 DNA segment, Chr 11, ERATO Doi 518, expressed 2.787755102 0.000053

Mm.297584 Gene model 73, (NCBI) 2.643835616 0.000056

Mm.257925 Homeodomain interacting protein kinase 3 2.93877551 0.000063

Mm.216313 CDNA sequence BC025031 2.255555556 0.000074

Mm.22670 Transformed mouse 3T3 cell double minute 2 3.529411765 0.000081

Mm.21646 Rho GTPase activating protein 19 3.188636364 0.000084

Mm.1843 Heat shock protein 1, alpha 3.917098446 0.000088

Mm.332522 WD repeat and FYVE domain containing 3 2.900735294 0.000101

Mm.100253 Ajuba 2.538593482 0.000102

Mm.257482 Apoptosis antagonizing transcription factor 3.429090909 0.000106

Mm.56337 Platelet-activating factor acetylhydrolase, isoform 1b 3.040625 0.000121

Mm.32305 Similar to hypothetical protein MGC955 3.657657658 0.000121

Mm.289914 DNA segment, Chr 1, ERATO Doi 396, expressed 3 0.000124

Mm.22876 Bleomycin hydrolase 2.546712803 0.000133

Mm.274463 Endothelin converting enzyme 1 3.612009238 0.000136

Mm.7087 Rabaptin, RAB GTPase binding effector protein 1 3.158102767 0.000137

Mm.22240 SH3 domain binding glutamic acid-rich protein-like 3 2.622994652 0.000148

Mm.297768 ADP-ribosylation factor 4 3.301310044 0.000148

Mm.18516 H3 histone, family 3B 2.987325729 0.000154

Mm.235891 Prion protein interacting protein 1 2.493243243 0.000157

Mm.271160 UPF3 regulator of nonsense transcripts homolog B (yeast) 3.284210526 0.00016

Mm.306429 Prion protein interacting protein 2 4.075177809 0.000163

Mm.120919 RIKEN cDNA F730047E07 gene 2.104575163 0.00019

Mm.197297 Transcribed locus, similar to RIKEN cDNA 8030498B09 2.592592593 0.000196

Mm.4263 Cystatin C 3.065013405 0.000196

Mm.215745 RIKEN cDNA 9230110M18 gene 2.813471503 0.000216

Mm.275742 RIKEN cDNA A330103N21 gene 2.682403433 0.000222

Mm.48179 Sideroflexin 4 2.670103093 0.000224

Mm.37199 Glutathione S-transferase, mu 1 3.883524442 0.000244

Mm.173728 Transcribed locus 2.55483871 0.000246

Mm.291548 Similar to tripartite motif-containing 43 2.449511401 0.00026

Mm.1249 Laminin, gamma 1 2.476727786 0.000266

Mm.34867 RAB27A, member RAS oncogene family 3.392197125 0.000279

Mm.293200 Formin-like 2 2.844086022 0.00033

Mm.162965 Transcribed locus 2.95045045 0.000343

Mm.227484 CDNA sequence BC065120 2.336283186 0.000347

Mm.138512 CDNA sequence BC024806 2.72 0.000359

Mm.328549 Eukaryotic translation initiation factor 4A1 2.162977867 0.000363

Mm.292742 RIKEN cDNA 2610101N10 gene 4.777777778 0.000364

Mm.1843 Heat shock protein 1, alpha 4.78 0.000366

Mm.257094 Integrin beta 3 binding protein (beta3-endonexin) 2.768683274 0.000375

Mm.295565 RIKEN cDNA F830004D09 gene 3.355491329 0.000385

Mm.308514 U1 small nuclear ribonucleoprotein 1C 2.195422535 0.000388

Mm.246869 RIKEN cDNA 8430423A01 gene 3.214285714 0.000409

Mm.259724 RIKEN cDNA 2010000I03 gene 3.314065511 0.00043

Mm.17917 EF hand domain containing 2 4.575789474 0.00043

Mm.173449 Transcribed locus, weakly similar to NP_081764.1 2.8203125 0.000432

Mm.399 Immediate early response 2 3.702297702 0.000437

Mm.41773 Transmembrane protein 9 3.642751843 0.000442

Mm.299292 Glutathione S-transferase, pi 1 2.178268251 0.000453

Mm.646 Tropomyosin 2, beta 2.629403476 0.000473

Mm.27831 RIKEN cDNA 1810003N24 gene 4.290380048 0.000473

Mm.21976 RIKEN cDNA 0610031J06 gene 4.248256625 0.000483

Mm.360326 Transcribed locus 2.901639344 0.000488

Mm.42604 Down syndrome critical region homolog 6 (human) 3.493377483 0.000492

p-value o0.0005 and fold difference X2.

In the order of p-value from lowest to highest.

H. Liu et al. / Biomaterials 27 (2006) 5978–5989 5987

ARTICLE IN PRESSH. Liu et al. / Biomaterials 27 (2006) 5978–59895988

differentiation pathways. In fact, we have demonstrated(see Taqvi et al., this issue) that poly(L-lactide)-basedscaffolds with similar pore sizes could also provide aconducive environment for ES cell hematopoiesis asassessed by flow cytometry and that scaffold architecturesignificantly influences differentiation efficacy. Similar geneexpression studies on ES cells cultured in scaffolds of otherbiomaterials as well as in scaffolds of varying micro-architecture could yield valuable information on howbiomaterials and culture parameters influence ES cells atthe molecular level.

5. Conclusions

Our results demonstrate that CytomatrixTM-based 3Dculture of ES cells, especially under dynamic conditions,increase ECM production as well as cell adhesion, resultingin increased signaling and enhanced expression of genes thatfunction in promoting cell differentiation. In addition,tantalum scaffold-based culture provides a more conducivemicroenvironment for ES cell differentiation by up-regulat-ing key growth factors, transcription factors and celldifferentiation related genes. However, which specificsignaling pathways are affected by alteration of those genesin 3D culture have not been identified in this study as morethan 80 genes involved in signal transduction were altered in3D culture. Further detailed and pathway specific geneexpression studies need to be performed in order to identifythe specific signaling pathways that play critical roles in thebeneficial effects of 3D-spinner and 3D-static culture duringES cell differentiation. Nevertheless, these results provide acomprehensive description of the effects of culture condi-tions on the gene expression profiles of mouse ES cells andpresent several important candidate genes that could beinvolved in providing the beneficial effects of 3D culture anddynamic environments on ES cell differentiation.

Acknowledgements

The authors would like to acknowledge Prof. Vishwa-nath R. Iyer, Institute of Cell and Molecular Biology, UTAustin and his lab for providing the microarray facility andhelpful technical advice. We thank Dr. Andras Nagy,Mount Sinai Hospital, Toronto for generously providingR1 murine embryonic stem cells, Shanna D. Maika, UTAustin for kindly providing us with STO cells. We wouldalso like to thank Jianwen Liu and Jian Gu at UT Austinfor their helpful comments.

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