IPA Analysis for Networks

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doi:10.1152/physiolgenomics.00197.200629:128-138, 2007. First published Dec 19, 2006;Physiol Genomics

Martin, Kateri A. Moore and Pierre CharbordGenevive Pitu, Alain Langonn, Nathalie Gallay, Luc Senseb, Michle T.Sebastien Chateauvieux, Jean-Laurent Ichant, Bruno Delorme, Vincent Frouin,

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Molecular profile of mouse stromal mesenchymal stem cells

Sebastien Chateauvieux,1 Jean-Laurent Ichante,2 Bruno Delorme,1

Vincent Frouin,2 Genevieve Pietu,2 Alain Langonne,1,3 Nathalie Gallay,1

Luc Sensebe,1,3 Michele T. Martin,2 Kateri A. Moore,4 and Pierre Charbord1

1Institut National de la Sante et de la Recherche Medicale, Equipe-ESPRI/EA-3855, Universite

Francois Rabelais, Faculte de Medecine, Tours; 2Commissariat a lEnergie Atomique, Service de Genomique Fonctionnelle,Evry; and 3Etablissement Francais du Sang-Centre-Atlantique, Tours, France; and 4Department of

Molecular Biology, Lewis Thomas Laboratory, Princeton University, Princeton, New Jersey

Submitted 6 September 2006; accepted in final form 17 December 2006

Chateauvieux S, Ichante J-L, Delorme B, Frouin V, Pietu G,

Langonne A, Gallay N, Sensebe L, Martin MT, Moore KA,

Charbord P. Molecular profile of mouse stromal mesenchymal stemcells. Physiol Genomics 29: 128 138, 2007. First published Decem-ber 19, 2006; doi:10.1152/physiolgenomics.00197.2006.We deter-mined a transcriptional profile specific for clonal stromal mesenchy-mal stem cells from adult and fetal hematopoietic sites. To identifymesenchymal stem cell-like stromal cell lines, we evaluated the

adipocytic, osteoblastic, chondrocytic, and vascular smooth muscledifferentiation potential and also the hematopoietic supportive (stro-mal) capacity of six mouse stromal cell lines from adult bone marrowand day 14.5 fetal liver. We found that two lines were quadripotentand also supported hematopoiesis, BMC9 from bone marrow andAFT024 from fetal liver. We then ascertained the set of genesdifferentially expressed in the intersection set of AFT024 and BMC9compared with those expressed in the union set of two negativecontrol lines, 2018 and BFC012 (both from fetal liver); 346 geneswere upregulated and 299 downregulated. Using Ingenuity software,we found two major gene networks with highly significant scores. Onenetwork contained downregulated genes that are known to be impli-cated in osteoblastic differentiation, proliferation, or transformation.The other network contained upregulated genes that belonged to twocategories, cytoskeletal genes and genes implicated in the transcrip-tional machinery. The data extend the concept of stromal mesenchy-mal stem cells to clonal cell populations derived not only from bonemarrow but also from fetal liver. The gene networks described shoulddiscriminate this cell type from other types of stem cells and helpdefine the stem cell state.

differentiation; hematopoiesis; cytoskeleton; transcription; gene net-work

DURING DEVELOPMENT, HEMATOPOIESIS takes place in sequentialsites (reviewed in Ref. 16). It develops during embryonic lifewithin the extraembryonic annex, the yolk sac, and within theintraembryonic region, the aorta-gonad-mesonephros (AGM)

region. During fetal life, it proceeds within the liver. Frombirth onward, bone marrow is the major, if not exclusive, siteof hematopoiesis in mammals. Hematopoietic stem cells(HSCs) migrate, via the bloodstream, from one site to the next.As early as the AGM stage, HSCs have acquired their essentialproperties of self-renewal and multipotentiality, giving rise toall blood lineages. It is in the fetal liver that HSCs show

maximal proliferation capacity: only at this stage is amplifica-tion of the HSC pool observed.

Cells from the microenvironment provide different nichesfor hematopoietic cells. In the HSC niche (reviewed in Refs. 1,24, 30, 48), the stemness, i.e., the balance between self-renewaland commitment, is insured by physical contact between theHSC and a stromal cell (i.e., hematopoietic supportive) andits associated extracellular matrix. In the bone marrow, many

recent experiments strongly suggest that the stromal compo-nent would be an osteoblastic-type cell or a highly specializedmicrovascular cell (1). In the fetal liver, fewer studies havetried to define the stromal component of the niche. We havesuggested (7) that a cell in epithelial-to-mesenchymal transi-tion would constitute such a stromal component; the final adultfates of such a cell would be hepatocytes and sinusoid vascularsmooth muscle cells that would no longer possess the stromalcapacity.

In all major hematopoietic sites (AGM, fetal liver, and bonemarrow), a new type of stem cells has been described: themesenchymal stem cells (MSCs) (6, 29, 36). MSCs are multi-potential cells that differentiate into adipocytes (A), osteoblasts

(O), chondrocytes (C), and vascular smooth muscle cells (V)(reviewed in Refs. 5, 13). It has been suggested that MSCs areidentical to stromal cells used as feeder layers for long-termcultures of HSCs (37). In this work, we searched for mesen-chymal clonal lines with A, O, C, and V differentiation poten-tial and with similar stromal capacity. We found that two lineshad such potential, one being from adult bone marrow, BMC9,and the other from the fetal liver, AFT024. We then tried toestablish the transcriptomic profile specific for stromal MSCsindependent of the hematopoietic site. To this end, we ascer-tained the set of genes differentially expressed in the intersec-tion set of AFT024 and BMC9 compared with those expressedin the union set of two negative control non-MSC lines. Thisset would account for the quadripotentiality and the stromal

potential, i.e., the specific capacity of this particular type ofstem cells.

MATERIALS AND METHODS

Cell Lines

Lines used in this work were either 14.5 days postcoitum (dpc) fetalliver lines (AFT024, 2012, 2018, and BFC012) provided by K.A.Moore or bone marrow lines (BMC9 and BMC10) kindly provided byJames E. Dennis (Case Western Reserve University, Cleveland, OH).All lines were immortalized using SV-40 large T-antigen. Largetemperature-sensitive T-antigen (TSa-58) lines were made by retro-viral transduction into the fetal liver stroma and clonally derived; the

Article published online before print. See web site for date of publication(http://physiolgenomics.physiology.org).

Address for reprint requests and other correspondence: P. Charbord, Labo-ratoire dHematopoiese, Faculte de medecine, batiment Dutrochet, 10 BvdTonnelle, Tours 37032, France (e-mail: [email protected]).

Physiol Genomics 29: 128138, 2007.First published December 19, 2006; doi:10.1152/physiolgenomics.00197.2006.

1094-8341/07 $8.00 Copyright 2007 the American Physiological Society128


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clonal nature was verified by Southern blot analysis, which detected asingle, unique proviral integration locus in the genomic DNA. Thebone marrow lines had been obtained from transgenic immortomicegenerated by embryonic stem (ES) cells transfected with thermosen-sitive T under the major histocompatibility complex promoter. Thelines were developed from isolated clones. Fetal liver cell lines werecultured at 33C in 5% CO2 in high-glucose DMEM with 10%(vol/vol) screened fetal calf serum (FCS, Hyclone), 0.1% -mercap-

toethanol, 2 mM L-glutamine, and antibiotics. Bone marrow cell lineswere cultured at 33C in 5% CO2 in -MEM with 10% FCS, 100IU/ml (50 ng/ml) -interferon, 2 mM L-glutamine, antibiotics, andantimycotics.

Differentiation Studies

Osteoblastic differentiation was induced by culture in DMEM(high glucose) medium with 10% FCS, 0.1 M dexamethasone, 2 mM-glycerophosphate, and 150 M ascorbate-2-phosphate. Cells wereseeded at 10,000 cells/cm2 and incubated for 21 days at 37C.Medium was changed every 4 days.

Adipogenic differentiation was induced by culturing in DMEM(high glucose) medium with 20% FCS, 1 M dexamethasone, 0.35M hydrocortisone, 0.5 mM isobutyl-methylxanthine (IBMX), 100

ng/ml insulin, and 60 M indomethacin. Cells were seeded at 20,000cells/cm2 and incubated for 12 days at 37C. Medium was changedevery 4 days.

Chondrogenic differentiation was obtained in micropellets (3 105 cells/pellet) incubated at 37C for 21 days in 500 l of chondro-genic medium composed of DMEM (high glucose) with 0.1 Mdexamethasone, 1 mM sodium pyruvate, 170 M ascorbic acid-2-phosphate, 350 M proline, 1 insulin-transferrin-selenium, and 10ng/ml transforming growth factor (TGF)-1. Medium was changedevery 4 days. RNA studies required the use of 2030 micropellets.

Vascular smooth muscle differentiation was obtained in long-termculture medium: McCoys 5A medium with 12.5% screened horseserum, 12.5% FCS, 20 M L-glutamine, 0.8 mM L-serine, 0.15 mML-asparagine, 1 mM sodium pyruvate, 5 mM sodium bicarbonate, 1M hydrocortisone, and antimycotics and antibiotics. Cells were

passaged at the end of the first week; during the two remaining weeks,medium was changed every 4 days.

Cytochemical staining. Alkaline phosphatase was evaluated, after4 and 15 days of culture in osteogenic medium, with the AlkalinePhosphatase Substrate Kit (Bio-Rad), added directly to the celllayer for 20 min at room temperature. For evaluation of themineralized matrix, the cell layer was fixed with 4% (vol/vol)formaldehyde, then stained by von Kossas stain using 5% (wt/vol)silver nitrate (Sigma) under ultraviolet light for 45 min, followedby 5% (wt/vol) sodium thiosulphate (Sigma) for 2 min: areas ofmineralization were evaluated with LUCIA software (Nikon). ForNile O Red staining (NRO), cells were fixed with 4% formalde-hyde and stained with 1 g/ml Nile-red-O (Sigma) for 30 min. Forsafranin O staining, micropellets were fixed with 4% formaldehydefor 24 h and then embedded in paraffin. Slides were stained with

0.1% (wt/vol) safranin O (Sigma) for 5 min and counterstainedwith 0.02% (wt/vol) Fast Green for 3 min.

Immunofluorescence. Cells were cultured on Lab-Tek chamberslides (Nunc). Confluent layers were fixed and permeabilized withmethanol for 10 min. Slides were incubated for 1 h with mouseanti-human smooth muscle myosin heavy chains (hSMV, Sigma),followed by Alexa-488-conjugated goat anti-mouse antibody (Inter-chim), for 30 min. After staining, slides were mounted with Vecta-shield DAPI (Vector) and examined with a Leica DMR microscope(Leica Microsystems).

RT-PCR. Total RNA was extracted using the RNeasy Tissue Kit(Qiagen) according to the manufacturers instructions. RNA concen-tration was determined by spectrophotometry at 260 nm, and RNAintegrity was evaluated by electrophoresis of 2 g of total RNA in 1%

(wt/vol) agarose and 1 Tris-acetate/EDTA. RT-PCR was performedon 10 ng of total RNA using the SuperScript One-Step RT-PCRSystem with Platinum (Invitrogen) and Applied Biosystems PCRsys-tem 2700. Primer sequences are as follows (F, forward; R, reverse):Gapdh (F: ggtgaaggtcggtgtgaacg; R: catcatacttggcaggtttctcc; 55C,761 bp); Acta2 (F: gctgttttcccatccatcgtg; R: tggtgatgatgccgtgttctatc;56.2C, 148 bp); Agc1 (F: tcctctccggtggcaaagaagttg; R: ccaagttc-cagggtcactgttaccg; 55C, 270 bp); Bglap1 (F: ctgagtctgacaaagccttc; R:

gctgtgacatccatacttgc; 60C, 313 bp); Des (F: cagatgagggagctggaggatc;R: tgggtgtgatatccgagagtgg; 56.1C, 449 bp); Fabp4 (F: ctcctcctcgaag-gtttacaaaatg; R: cctttcataacacattccaccacc; 56C, 387 bp); Lpl (F:tgtaactgttctgccctcccc; R: ttctctcttgacagggcggc; 55C, 456 bp); Pparg(F: tcggaatcagctctgtggacc; R: aacagcttctccttctcggcc; 56C, 538 bp).For real-time quantitative RT-PCR, reverse transcription was per-formed using the HighCapacity cDNA Archive Kit (Applied Biosys-tems) on 3 g of total RNA; PCR was then performed using theTaqman-Low-Density Arrays Microfluidic Cards (Applied Biosys-tems), according to the manufacturers instructions.

Western blotting. For Western blotting, described in detail in Ref.9, primary antibodies were mouse anti-human monoclonal antibodies(mAbs) from Sigma-Aldrich that are cross-reactive with mouse pro-teins: anti-vinculin (Vin11-5), anti-caldesmon (hCald), and anti-smooth muscle myosin heavy chains (hSMV). Secondary antibody

was goat anti-mouse IgG conjugated to horseradish peroxidase (Bio-Rad). Revelation by chemiluminescence was performed by ECLplusWestern Blotting Detection Kit (Amersham Biosciences) and acqui-sition with Chemi-Smart 2000 using Chemocapt software(Vilbert-Lourmat).

Flow cytometry. Cells were detached using phosphate-bufferedsaline (PBS) with 1 mM EDTA. Primary antibodies were purified ratanti-mouse mAbs from BD Biosciences: CD34 (RAM34), CD44(IM-7), CD45 (30F-11), CD49d (R1-2AKR), CD49e (5H10-27),CD105 (MJ7/18), CD106 (429), and Sca-1 (D7) or their negativecontrols (rat IgG1, IgG2a, and IgG2b). Secondary antibody wasphycoerythrin (PE)-conjugated goat anti-rat antibody. Cells werepassed through a FACSCalibur flow cytometer (Becton-Dickinson)using a 488-nm argon laser. Samples were analyzed by collecting10,000 events using Cell-Quest software (Becton-Dickinson).

Hematopoiesis Supportive (Stromal) Capacity

Cobblestone area-forming cell. The hematopoietic population ofprecursors was purified from 4- to 6-wk-old C57Bl/6J mouse cells.Sca1/Lin cells were isolated following, first, depletion of lineage-positive cells using a lineage cell depletion kit (Miltenyi) and, second,isolation of Sca1 cells with a PE selection kit (EasySep) usinganti-Sca1 antibody conjugated to PE (D7, BD Biosciences). Theprotocol for the study was submitted to and approved by the localEthical Committeee. The purity was 95%, as evaluated by flowcytometry. Sca1/Lin cells were plated on irradiated (15Gy) con-fluent layers of AFT024 or BMC9 grown on 96-well plates, using6 24 replicas of 7 cell concentrations (1200 cells/well). Cobblestonearea-forming cell (CAFC) frequency was determined by limit-dilution

analysis using Poisson statistics.Flow cytometry. Analysis of hematopoietic precursors co-culti-vated for 5 wk with the stromal layers was carried out using flowcytometry. Cells were labeled with rat anti-mouse mAbs from BDBiosciences: anti-CD45 (30-F11) conjugated to allophycocyanin(APC), anti-Sca-1 (D7) conjugated to PE, and antibodies conjugatedto FITC, either CD4 (GK1.5) CD8a (53-6.7) CD45R (B220), orCD11b (M1/70), CD51 (RMV-7), CD14 (55-3), and Ter119(Ter-119).

Gene Screening by CEA Chip

The mouse CEA chip consists of 13,060 cDNA clones from earlymouse embryo libraries constructed by the National Institute on Aging(NIA; http://www.nia.nih.gov) representing 11,000 genes. It also

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includes positive [actin, tubulin, oligo(dT), cot-1 DNA] and negative(Tris-EDTA/DMSO) controls present many times in the array forquality control. Microarrays were prepared by spotting PCR productsas previously described. The DNA chip used for this experiment isdescribed and available at Gene Expression Omnibus (GEO;GPL3438 and GPL3439).

RNA extraction. For each line, RNA was extracted from twoindependent cultures. Total RNA was isolated using the Trizol reagent

(Invitrogen) and dissolved in RNase-free water. The quality of RNAwas controlled using an Agilent 2100 Bioanalyzer (Agilent Technol-ogies), and concentration was measured by absorbance at 260 nm. Foreach target preparation, 20 g of total RNA were reverse transcribedusing Superscript II RT (Life Technologies) in the presence of anoligo(dT)-primed reaction and an amino-modified nucleotide (amino-allyl-dUTP). Amino-modified cDNAs were purified through a Micro-con Centricon 30 microconcentrator (Amicon) and ethanol precipi-tated. In a second step, monofunctional forms of Cy3 and Cy5 dyes(Amersham Biosciences) were coupled with the purified amino-modified cDNAs. Unincorporated fluorescent molecules and saltswere removed through the Microcon Centricon 30. Labeled cDNAwas mixed with 10 g of poly(A) RNA (Boehringer), 10 g of tRNA(Life Technologies), and 10 g of mouse Cot1 DNA (Life Technol-ogies). Purified labeled targets were hybridized to the array overnight

as previously described (3). The cell lines 2018, BFC012, and BMC9were each compared with AFT024. Each comparison was performedfour times in both labeling orientations (8 hybridizations per compar-ison, 4 dye swaps).

Microarray data processing. Fluorescence intensities of Cy3 andCy5 were measured separately at 532 and 635 nm, respectively, witha laser scanner (Axon GenePix 4000A). Image analysis was per-formed with GenePix Pro 4.0 software (Axon). Spots with obviousblemishes were flagged. Genes with null intensity values and lowmean intensity were also annotated with a specific flag and excludedfrom the list of validated differentially expressed genes. Statisticalanalysis of experimental data was performed after an intensity-depen-dent LOWESS normalization (47) with BioConductor/Limma (ver-sion 1.8.16) (39), using a standard ANOVA performed on the loga-rithm of gene expression data without background subtraction as

described in Ref. 12. We did not apply a threshold on the ratio valuesof gene expression but instead used the t-test to determine significanceas such: results significantly different from 1 (P value 0.05) weredetermined from the eight values obtained for each comparison.The microarray data set used for this analysis is described andavailable from GEO (GSE4491).

Gene network analysis. The interactions between genes identifiedas differentially expressed and all other genes were investigated usingthe Ingenuity Pathways Analysis (IPA). A series of networks wasgenerated; a network is defined by IPA as the reflection of allinteractions of a given protein defined in the literature. The interactionindicates physical association or consists of induction/activation orrepression/inactivation/degradation of one gene product by the other,eventually through another intermediary molecule (indirect interac-tion). The program calculates a statistical score based on a right-tailed

Fishers exact test that calculates the fit of each network to the set ofstudied genes. A score 2 indicates that there is a less than 1 in 100chance that the studied genes are assembled into the network becauseof random chance. We considered only the networks with the highestscores (50). We introduced in the analysis two sets: that of upregu-lated genes and that of downregulated genes. The two major networksfor up- and downregulated genes were then compared to find out theinteractions among genes belonging to either network.

RESULTS

Previous studies have shown that the four 14.5 dpc fetal liverlines (AFT024, 2012, 2018, and BFC012) varied greatly intheir ability to support hematopoiesis, with AFT024 being the

best supporter (18). The mesenchymal differentiation potentialof the fetal liver lines was not evaluated in previous works.On the contrary, in another report, the adult bone marrowline BMC9 was shown to be tripotent (with A, O, and Cdifferentiation potential) and supportive for osteoclasts,while BMC10 was deficient in both A differentiation andosteoclast support (14).

AFT024 and BMC9 Are Quadripotent Mesenchymal Lines

After 12 days in adipogenic medium, many AFT024 andBMC9 cells contained large (5 m in diameter) NRO

vesicles (Fig. 1A), and adipocytic markers (Fig. 2A) wereinduced (lipoprotein lipase; Lpl) or increased [fatty acid-bind-ing protein (Fabp4) and peroxisome proliferator-activated re-ceptor- (Pparg)]. After 21 days in osteogenic medium, manyvon Kossamineralized areas were apparent (Fig. 1A), and forAFT024, the osteocalcin (Bglap) osteoblastic marker was in-creased (Fig. 2A). Alkaline phosphatase was significantly in-creased in both lines at day 4 (P 0.05) and day 15 (P 0.001) (Fig. 2B). After 21 days in chondrogenic culture con-

ditions, safranin O well-formed micropellets were apparent(Fig. 1A), and the aggrecan-1 (Agc1) chondrocytic marker wasclearly induced in both lines (Fig. 2A). After 21 days of cellsbeing in long-term culture medium inducing V differentiation,immunofluorescence studies indicated the presence of micro-filaments containing smooth muscle myosin in most AFT024cells and about one-half of BMC9 cells (Fig. 1B). -Smoothmuscle actin (Acta2) transcripts in AFT024 and desmin (Des)transcripts in both lines were slightly increased (Fig. 2A).Western blotting studies indicated that the smooth musclemyosin heavy chain SM1 was enhanced in AFT024, h-caldes-mon was clearly induced in both lines, and metavinculin wasdetected in both (Fig. 2C). Finally, all cells from both lines

expressed, at high a level, CD106, Sca-1, and CD49e; on theother hand, there was no expression of CD45, CD34, CD49d,and CD90 (not shown).

In 2012 and BMC10 cells, after A differentiation, mostNRO vesicles (Fig. 1A) were of small size, and Fabp4 andPparg were enhanced, while Lpl was not detected in BMC10(Fig. 1B). After O differentiation, many von Kossa mineral-ized areas were apparent (Fig. 1A), and Bglap was increased(Fig. 2A). Alkaline phosphatase was significantly increased atday 4 (P 0.001) in 2012 and day 15 (P 0.001) in both lines(Fig. 2B). After C differentiation, micropellets contained fewsafranin O areas (Fig. 1A). After V differentiation, Acta2 andDes transcripts remained unchanged (but the band was faint in2012) (Fig. 2A); h-caldesmon, SM1, and metavinculin were

increased in 2012, but h-caldesmon and SM1 remained barelydetectable in BMC10 (Fig. 2C). The immune phenotype was asdescribed for AFT024 and BMC9 (not shown).

In 2018 and BFC012, after A differentiation, few cells withsmall-sized NRO vesicles were detected (Fig. 1A); in 2018,but not BFC012, Lpl, Fabp4, and Pparg were induced (Fig.2A). After O differentiation, von Kossa mineralized areaswere not detected in either lines (Fig. 1A), but in 2018, Bglapwas detected before differentiation and unchanged after(Fig. 2A). Alkaline phosphatase was significantly increasedat day 4 (P 0.001) in 2018 and day 15 (P 0.001) in bothlines (Fig. 2B), which suggested that both lines were able todifferentiate, more or less readily, into O but were defective

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for mineralization. After C differentiation, micropellets con-tained no safranin O areas (Fig. 1A), and Agc1 inductionwas weak in BFC012 (Fig. 2A). After V differentiation, Destranscripts were induced in 2018, but barely in BFC012, andActa2 was unchanged (Fig. 2A); a faint h-caldesmon band wasapparent, but no metavinculin, while SM1 was unchanged inBFC012 (Fig. 2C). CD49e expression was low in both lines;Sca-1 was not detected in BFC012, and CD34 was expressed inboth lines (not shown).

In conclusion, AFT024 and BMC9 were clearly quadripo-tent and showed an immune phenotype of murine MSCs. Allother lines showed impaired differentiation at one or several

levels. The lines with the most impaired differentiation poten-tial were 2018 and BFC012; these lines also showed unusualexpression of some of the membrane markers.

AFT024 and BMC9 Are Stromal Lines

The hematopoietic supportive ability was studied in bothlines by seeding irradiated cells with bone marrow mouseSca1/Lin cells (Fig. 3). The CAFC frequency (Fig. 3, Cand

D) from two HSC enrichments after 5 wk was 1/401/50 and1/1101/160 for AFT024 and BCM9, respectively. Flow cy-tometry studies (Fig. 3B) indicated the persistence of immature

Fig. 1. Differentiation potential of the celllines, cellular markers. A: histochemistry (alllines, 1 representative experiment of 3). Thefollowing is presented for each line: mor-phology (phase contrast) of cells cultured in

proliferation medium, staining by von Kossastain after 21 days in osteogenic medium,staining by Nile Red O after 12 days inadipogenic medium, and staining by safraninO on micropellets maintained for 21 days inchondrogenic medium. Bar 100 m.

B: immunofluorescence for AFT024 andBMC9 cells stained with anti-smooth muscle(SM) myosin; for vascular smooth musclecell (V) differentiation, cells were culturedfor 21 days in the long-term culture medium,before fixation and staining.




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Sca1/CD45 hematopoietic cells along with more matureCD11b/CD45 granulocytes, CD14/CD45 monocytes,and CD51/CD45 megakaryocytes, without significant dif-ference between the two cell lines. Very few TER119/CD45

erythroid cells were detected on BMC9. CD4/CD45, CD8/

CD45,

or CD45R

/CD45

lymphoid cells were not detected.The presence of megakaryocytes, polymorphs, and monocyteswas confirmed by cytology after May Grunwald Giemsa stain-ing (Fig. 3A). In conclusion, both lines displayed hematopoi-etic support, with an advantage for AFT024 in terms of CAFCfrequency.

Molecular Profile of Stromal MSCs

Results from the above cellular studies indicated thatAFT024 and BMC9 were adequate models for stromal multi-potential MSCs, whereas 2018 and BFC012 with severelydefective stromal and differentiation potential were negativecontrol lines. To determine the molecular profile specific for

stromal multipotential MSCs independent of the hematopoieticsite, we ascertained the set of genes differentially expressed inthe intersection set of AFT024 and BMC9 compared with thoseexpressed in the union set of the two negative control lines2018 and BFC012. The lines BMC10 and 2012, with partially

defective differentiation and stromal potential, were not con-sidered in the analysis. Our strategy was, first, to determine theset of genes included in the union of genes expressed by 2018and BFC012 (U1 2018 BFC012); second, to subtract thisunion set from genes expressed by AFT024 (S1 AFT024 U1) and by BMC9 (S2 BMC9 U1); and, third, todetermine the intersection of S1 and S2 (S3 S1 S2). Therewere 346 upregulated and 299 downregulated genes in S3.Functional classification is shown in Fig. 4. Hierarchical clus-tering validated our strategy, the genes up- or downregulated inBMC9 (2 distinct extractions, 8 dye swaps) showing thegreatest similarity to those in AFT024, whereas those inBFC012 showed the greatest dissimilarity (Fig. 5).

Fig. 2. Differentiation stromal potential of the cell lines, mo-lecular markers. A: RT-PCR. Expression of differentiation-specific transcripts for adipocytes (Lpl, Fabp4, and Pprag),osteoblasts (Bglap), chondrocytes (Agc1), and vascular smoothmuscle cells (Des and Acta2). Housekeeping gene Gapdh.Before extraction, cells were cultured in respective media asindicated in Fig. 1. C, control medium; I, induction medium. B:alkaline phosphatase concentration as expressed by the ratio of

day 4 to day 0 and day 15 to day 0. Statistical significance (8experiments per time point for each line) was evaluated usingANOVA: *P 0.05 and **P 0.01. C: Western blotting.Expression of vascular smooth muscle-specific proteins show-ing the induction or not of the 200-kDa smooth muscle myosinheavy chain (SM1), of h-caldesmon (h-Cald), and of metavin-culin (MetaVcl). -Act, -actin.




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Supplemental Table 1 (supplemental data are available at theonline version of this article) gives the list of downregulatedgenes belonging to the following categories: cytoskeleton,transcription and chromatin remodeling, signaling, adhesion,trafficking, metabolism, cell cycle and apoptosis, protein syn-thesis and degradation, and other. Study of gene networksusing Ingenuity software revealed a major network of 35genes, with a highly significant score of 64 (Network 1,Fig. 6A). Ten of the downregulated genes in this network coded

for proteins implicated positively in osteogenic differentiation,proliferation, or transformation: protooncogene protein c-fos(Fos), parathyroid hormone-related protein (Pthlh), ad-renomedullin (Adm), receptor activity-modifying protein 2(Ramp2), apoptosis regulator Bcl-2 (Bcl2), ezrin (Vil2), estro-gen receptor 1 (Esr1), proline-rich nuclear receptor co-activa-tor 1 (Pnrc1), guanine nucleotide-binding protein G, -subunit(Gnas), and regulator of G protein signaling 2 (Rgs2).

Supplemental Table 2 lists the upregulated genes groupedinto the same categories as in Supplemental Table 1. Study ofgene networks using the Ingenuity software revealed a majornetwork of 35 genes, with a highly significant score of 56(Network 2, Fig. 6B). Most interactions in this network were

direct and consisted of physical association or induction. Tran-scripts belonged to two categories, transcripts for cytoskeletalmolecules and transcripts implicated in the regulation of thetranscriptional machinery (including chromatin remodeling).The genes of this network encoding proteins implicated in thecytoskeleton were as follows: the structural proteins tropomyo-sins (Tpm3, Tpm1), moesin (Msn), cytoplasmic 1 actin (Actb),cytoplasmic 2 actin (Actg1), the molecular chaperones foractin and tubulin, T-complex protein 1 subunit- (Cct3),

- (Cct5), and - (Cct7), and molecules involved in the regu-lation of microfilament or microtubule assembly/dynamics,rhophilin (Rhpn2), transforming protein RhoA (Rhoa), phos-pholipase D1 (Pld1), myosin regulatory light chain MRCL2(Mrlc2), protein diaphanous homolog 3 (Diaph3), and ADP-ribosylation factor 1 (Arf1). Gene Ontology analysis confirmedthe significance (P 0.02 by Fishers exact test) of theoverrepresentation of biological processes, cellular compo-nents, and molecular functions involved in cytoskeletal orga-nization. The complete list of upregulated genes (SupplementalTable 2) confirmed the presence of many cytoskeletal genesnot included in the network described above. The molecules ofthe network involved in the regulation of transcription were as

Fig. 3. Stromal potential of AFT024 and BMC9. A: cytology of hematopoietic cells (Sca1

/Lin

) cultured for 5 wk on either line, showing the presence ofmegakaryocytes, polymorphs, and monocytes. B: flow cytometry studies performed on hematopoietic cells cultured for 5 wk on either line. C: cobblestone areaformation from hematopoietic cells after 5 wk in culture. D: cobblestone area-forming cell (CAFC) frequency as measured after 5 wk for hematopoietic cellscultured at limit dilution.




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follows: SWI/SNF-related matrix-associated actin-dependentregulator of chromatin (Smarcc1), the splicing factors hetero-geneous nuclear ribonucleoprotein-A1 (Hnrpa1), -D0 (Hnrpd),-U (Hnrpu) and -K (Hnrpk), the arginine/serine-rich proteins 1and 3 (Sfrs1, Sfrs3), ruvB-like 1 (Ruvbl1), actin-like protein6A (Actl6a), putative RNA-binding protein 3 (Rbm3), GATA-binding protein 2 (Gata2), four and a half LIM domains protein2 (Fhl2), zinc finger protein 638 (Znf638), high-mobility groupnucleosome-binding domain-containing protein 2 (Hmgn2),protein flightless-1 homolog (Flii), and Cullin-1 (Cul1). Someof the cytoskeletal molecules are known to be associated to

molecules involved in the transcription machinery: Rhoa isfunctionally associated to Fhl2, as activated Rhoa induces thetranslocation of Fhl2 to the nucleus and its subsequent activa-tion (31); Actl6a, Ruvbl1, and Smarcc1 are part of molecularcomplexes associating transcriptional regulators to moleculesof the cytoskeleton such as Actb (15, 34). Two transcripts, Fhl2and Ruvbl1, are implicated in the Wnt signaling pathway,known to modulate the transcriptional transactivation of-catenin in association with LEF1/TEF factors (45).

Certain molecules of the network of downregulated genes(Network 1) are known to be physically associated to those of

Fig. 4. Functional classification of genes up- and downregulated in mesenchymal stem cells (MSCs). This classification was performed after analysis of the datain the literature for each of the genes.

Fig. 5. Hierarchical clustering of genes up-and downregulated in MSCs. Each columnindicates the level of gene expression inBMC9, 2018, and BFC012, as related to that inAFT024. Color scale indicates the degree ofsimilarity. Gene clusters are shown at left andrightsides (for upregulated and downregulatedgenes, respectively). The Sr-2 red box includes11 genes present in the network of upregulatedgenes (shown in Fig. 6B).




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the network of upregulated genes (Network 2) (Fig. 6): villin 2(Network 1) to moesin and cytoplasmic 1 actin (Network 2);and NF-B inhibitor- and Fos (Network 1) to different het-erogeneous nuclear ribonucleoproteins and to cytoplasmic 2actin, ADP-ribosylation factor 1, and RhoA (Network 2) (2, 10,11, 17, 19, 22, 32, 44). Eleven (of 35) molecules of the networkof upregulated genes were localized in a specific cluster, Sr-2,that contained 46 genes (Fig. 5).

The molecules included in the two networks and theirinteracting partners are listed in Supplemental Table 4.

DISCUSSION

Our study indicates that two mouse mesenchymal clonallines, one from bone marrow (BMC9) and the other from fetal

liver (AFT024), possess the characteristics of stromal MSCs.Both lines were able to differentiate into adipocytes, mineral-izing osteoblasts, chondrocytes, and vascular smooth musclecells and supported Sca1/Lin mouse bone marrow hemato-poietic precursors, allowing the generation of cobblestoneareas and the differentiation of myeloid precursors. On thecontrary, in the other lines, the mesenchymal differentiationpotential was impaired at one or several levels. The differen-tiation defect was most severe in 2018 and BFC012. Theselines gave rise to few adipocytes, did not generate mineralizingosteoblasts, gave, under chondrogenic condition, loose aggre-gates that were safranin O negative, and expressed, after Vdifferentiation, low amounts of h-caldesmon. In addition, it has

been shown in a previous study that none of these two linesallowed the maintenance of HSCs (18).

It has been suggested that the two populations, that of MSCs(isolated by their adherence to plastic and containing stem cells/progenitors for the A, O, C lineages) and that of stromal cells(used as feeder layers for long-term cultures of HSCs), areidentical (37). This hypothesis has been sustained for culture-expanded bone marrow primary human MSCs (28). Our studyextends this concept of stromal MSCs to clonal cell populationsderived not only from bone marrow but also from fetal liver.

To determine the transcriptomic profile specific for stromalmultipotential MSCs independent of the hematopoietic site, weascertained the set of genes differentially expressed in theintersection set of AFT024 and BMC9 compared with those

expressed in the union set of the two negative control lines,2018 and BFC012. We found that 645 transcripts were specif-ically regulated in the two stromal multipotential cell lines,with a similar number of up- and downregulated genes.

Some of the upregulated transcripts appeared to be of specialinterest and already have been described in the literature onstromal cells: the serine/threonine kinase NLK (Nlk) and theJumonji protein 1a and 2 (Jarid1a, Jarid2), because of theirdemonstrated role as stromal mediator and differentiating fac-tor for stromal cells (23, 25), and the lymphocyte-specificadapter protein Lnk (Lnk), because of its implication in theinteraction between HSCs and cells from the microenviron-ment (41).

Fig. 6. Studies of gene networks up- and downregulated in MSCs. A: major network (Network 1) of genes downregulated in MSCs (as given by the Ingenuitysoftware). The no. under each gene name indicates the mean log signal ratio for AFT024 (2018 BCF012); similar values were obtained for BMC9 (2018 BCF012). B: major network (Network 2) of genes upregulated in MSCs. A and B: regular line for physical association, arrow line for induction/activation,blunt-ended line for repression/inactivation/degradation, and discontinuous line for indirect interaction. Details about the interactions are given in SupplementalTable 4.




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As shown in Table 1, 42 transcripts in our set of upregulatedgenes were also found upregulated in other embryonic or adulthematopoietic or neural stem cells (4, 21, 27, 33, 38, 42, 43,49). Such transcripts may be characteristic of the stem cell state(50). Studies using short interfering RNA (20, 40) shouldconfirm this hypothesis.

Because our gene chip encompasses about only one-third ofthe known mammalian genome, the number of up- and down-regulated genes might be larger than what is described here. Inparticular, some categories found in other genetic screens asimplicated in stromal support (8) are insufficiently represented

in the chip used here (especially proteoglycans and chemo-kines).We chose to study specific clones that were immortalized

using a temperature-sensitive SV-40 T-antigen for the follow-ing reasons. 1) These clones have been studied in detailpreviously (14, 18), either for their stromal capacity (fetal liverlines) or for their differentiation potential (bone marrow lines).2) The introduction of the viral sequence would insure suffi-cient proliferation, in particular when studying chondrogenicdifferentiation using the micropellet technique, requiring largecell numbers. 3) Mouse cells immortalized by T show aphenotype comparable to nontransduced cells (9).

To assess the potential influence of viral genes on theexpression of cell genes, we have recently compared, using

microfluidic cards from Applied Biosystems, the expression of380 transcripts in clones derived from primary cultures ofmouse bone marrow MSCs vs. BMC9 and BMC10. We havefound that 7% of the transcripts were up- or downregulated incells with large T. The studied transcripts belonged to severalcategories. The least affected category was that of cytoskeletalcomponents (only 3% of the genes in this category weresignificantly modulated). On the other hand, the most affectedcategory was that of molecules involved in cell cycle andapoptosis: 39% of the studied cyclins, cyclin inhibitors, andapoptosis inhibitors were upregulated in BMC9 and BMC10.Molecules implicated in the transcriptional machinery wereonly marginally affected (6%). These data indicate that the

expression of genes belonging to the cell cycle and apoptosiscategory (see Supplemental Tables 1 and 2) may have beeninfluenced by the viral sequence insertion. However, mostgenes present in the networks (vide below) are probablyminimally influenced by the presence of T.

Using the Ingenuity software, we found two major networkswith highly significant scores 50. The network of 35 down-

regulated genes contained 10 transcripts positively implicatedin osteoblastic differentiation, proliferation, or transformation.These data suggest that the intersection set of AFT024 andBMC9 is representative of bona fide undifferentiated cells, incontrast to the set of 2018 and BFC012, which appears torepresent cells already committed to the osteogenic pathwayalbeit unable to complete it by mineralization when placed inan osteogenic condition.

The network of 35 upregulated genes belonged to twocategories, transcripts for cytoskeletal molecules and tran-scripts implicated in the regulation of the transcriptional ma-chinery (including chromatin remodeling). Cytoskeletal mole-cules included structural components of actin-based cytoskel-eton, chaperones for actins and tubulins, and proteins involvedin the signaling pathways leading to the assembly/disassemblyof microtubules and microfilaments. Some of the moleculesimplicated in the transcriptional machinery have been detectedin protein complexes associated with cytoskeletal components,such as the NuA4 histone acetylase complex (15) or the BAF53complex (34).

Networks have not been emphasized in previous transcrip-tomic studies on stem cells (4, 21, 27, 33, 35, 38, 40, 42, 43, 46,49). The networks described in the present study may serve asa basis for future experiments. First, one may assess whetherthe same networks are found in MSCs from primary cultures(polyclonal and clonal cultures). Second, one may investigatewhether the hyperexpression of some of the network cytoskel-

etal components (either structural, such as moesin or cytoplas-mic actin 1, or regulatory, such as RhoA) induces the hyper-expression or downregulation of some of the molecules impli-cated in the transcription machinery and in the differentiationpathways. As a final point, it will be essential to verify whetherthe hyperexpression of a cytoskeletal component belonging tothe gene network of upregulated molecules improves or ham-pers the differentiation and/or stromal potentials of the trans-duced cells. Genetic regulatory networks provide essentialinformation on the generation of the different cell types (26).Future experiments should indicate whether the gene networkspresently described are genetic regulatory networks (i.e., in-clude molecules involved in positive or negative regulatoryloops) that determine the maintenance in a nondifferentiated

state of this particular stem cell type.In conclusion, this study describes gene networks for stro-

mal MSCs from the two major hematopoietic sites that shouldhelp discriminate this cell type from other stem cells (ES,neural, hematopoietic, etc.) and help define the stem cell state.

ACKNOWLEDGMENTS

We thank Jorge Domenech, Olivier Herault, and Cyrille Petat for helpfuldiscussion on different methodological aspects of this work.

GRANTS

This work was supported by grants from the European Union (IntegratedProject Genostem no. 503161), from Fondation de France (no. 2002002384),

Table 1. Stemness gene candidates

Trafficking Cytoskeleton Metabolism Signaling

Cops4 Actb Acadm CatnalKpna2 Cct3 Fasn Hdgf Laptm5 Cct5 Nme2 Ly6eSnx2 Tpm3 Slc25a5 M6prSyt11 Mlc1Tapbp Ppp2r5c

Ywhaq

Cell Cycle andApoptosis

Protein Synthesisand Degradation

Transcription andChromatin Remodeling

Ccnb1 Eif4g2 Cpsf3Ccng1 Hspa8 Gata2Diablo Pigf Hmgn2Hipk3 Psmb4 Hnrpa1Nasp Psmc5 HnrpuCcnb1 Sdf4 Psip1

PtmaSfrs3

Transcripts expressed in stromal mesenchymal stem cells (MSCs) and inother stem cell types. For details, see Supplemental Table 3 (supplemented

data are available at the online version of this article).




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from Association de Recherche sur le Cancer (no. 5827), from Electricite deFrance, and from the National Heart, Lung, and Blood Institute (NIH-HL-58739). S. Chateauvieux was supported in part by the Societe FrancaisedHematologie.

REFERENCES

1. Adams GB, Scadden DT. The hematopoietic stem cell in its place. NatImmun 7: 333337, 2006.

2. Adilakshmi T, Laine RO. Ribosomal protein S25 mRNA partners withMTF-1 and La to provide a p53-mediated mechanism for survival ordeath. J Biol Chem 277: 41474151, 2002.

3. Benchaouir R, Rameau P, Decraene C, Dreyfus P, Israeli D, Pietu G,Danos O, Garcia L. Evidence for a resident subset of cells with SPphenotype in the C2C12 myogenic line: a tool to explore muscle stem cellbiology. Exp Cell Res 294: 254268, 2004.

4. Bhattacharya B, Miura T, Brandenberger R, Mejido J, Luo Y, YangAX, Joshi BH, Ginis I, Thies RS, Amit M, Lyons I, Condie BG,Itskovitz-Eldor J, Rao MS, Puri RK. Gene expression in human em-bryonic stem cell lines: unique molecular signature. Blood 103: 29562964, 2004.

5. Bianco P, Gehron Robey P. Marrow stromal stem cells. J Clin Invest105: 16631668, 2000.

6. Campagnoli C, Roberts IA, Kumar S, Bennett PR, Bellantuono I, FiskNM. Identification of mesenchymal stem/progenitor cells in human first-trimester fetal blood, liver, and bone marrow. Blood98: 23962402, 2001.

7. Chagraoui J, Lepage-Noll A, Anjo A, Uzan G, Charbord P. Fetal liverstroma consists of cells in epithelial-to-mesenchymal transition. Blood101: 29732982, 2003.

8. Charbord P, Moore K. Gene expression in stem cell-supporting stromalcell lines. Ann NY Acad Sci 1044: 159167, 2005.

9. Charbord P, Oostendorp R, Pang W, Herault O, Noel F, Tsuji T,Dzierzak E, Peault B. Comparative study of stromal cell lines derivedfrom embryonic, fetal, and postnatal mouse blood-forming tissues. Exp

Hematol 30: 12021210, 2002.10. Chen CY, Xu N, Shyu AB. Highly selective actions of HuR in antago-

nizing AU-rich element-mediated mRNA destabilization. Mol Cell Biol22: 72687278, 2002.

11. Davis M, Hatzubai A, Andersen JS, Ben-Shushan E, Fisher GZ,Yaron A, Bauskin A, Mercurio F, Mann M, Ben-Neriah Y. Pseudosub-strate regulation of the SCF(beta-TrCP) ubiquitin ligase by hnRNP-U.Genes Dev 16: 439451, 2002.

12. Decraene C, Benchaouir R, Dillies MA, Israeli D, Bortoli S, Rochon C,Rameau P, Pitaval A, Tronik-Le Roux D, Danos O, Gidrol X, GarciaL, Pietu G. Global transcriptional characterization of SP and MP cellsfrom the myogenic C2C12 cell line: effect of FGF6. Physiol Genomics 23:132149, 2005.

13. Dennis JE, Charbord P. Origin and differentiation of human and murinestroma. Stem Cells 20: 205214, 2002.

14. Dennis JE, Merriam A, Awadallah A, Yoo JU, Johnstone B, CaplanAI. A quadripotential mesenchymal progenitor cell isolated from themarrow of an adult mouse. J Bone Miner Res 14: 700709, 1999.

15. Doyon Y, Cote J. The highly conserved and multifunctional NuA4 HATcomplex. Curr Opin Genet Dev 14: 147154, 2004.

16. Dzierzak E, Oostendorp R. Hematopoietic stem cell development inmammals. In: Hematopoiesis. A Developmental Approach. Oxford, UK:Oxford Univ. Press, 2001, p. 209217.

17. Gutkind JS. Cell growth control by G protein-coupled receptors: fromsignal transduction to signal integration. Oncogene 17: 13311342, 1998.

18. Hackney JA, Charbord P, Brunk BP, Stoeckert CJ, Lemischka IR,Moore KA. A molecular profile of a hematopoietic stem cell niche. ProcNatl Acad Sci USA 99: 1306113066, 2002.

19. Hay DC, Kemp GD, Dargemont C, Hay RT. Interaction betweenhnRNPA1 and IkappaBalpha is required for maximal activation of NF-kappaB-dependent transcription. Mol Cell Biol 21: 34823490, 2001.

20. Ivanova N, Dobrin R, Lu R, Kotenko I, Levorse J, DeCoste C, SchaferX, Lun Y, Lemischka IR. Dissecting self-renewal in stem cells with RNAinterference. Nature 442: 533538, 2006.

21. Ivanova NB, Dimos JT, Schaniel C, Hackney JA, Moore KA, Lemis-chka IR. A stem cell molecular signature. Science 298: 601604, 2002.

22. Johnston IM, Spence HJ, Winnie JN, McGarry L, Vass JK, MeagherL, Stapleton G, Ozanne BW. Regulation of a multigenic invasionprogramme by the transcription factor, AP-1: re-expression of a down-regulated gene, TSC-36, inhibits invasion. Oncogene 19: 53485358,2000.

23. Kitajima K, Kojima M, Nakajima K, Kondo S, Hara T, Miyajima A,Takeuchi T. Definitive but not primitive hematopoiesis is impaired injumonji mutant mice. Blood 93: 8795, 1999.

24. Kopp HG, Avecilla ST, Hooper AT, Rafii S. The bone marrow vascularniche: home of HSC differentiation and mobilization. Physiology Be-thesda 20: 349356, 2005.

25. Kortenjann M, Nehls M, Smith AJ, Carsetti R, Schuler J, Kohler G,Boehm T. Abnormal bone marrow stroma in mice deficient for nemo-likekinase, Nlk. Eur J Immunol 31: 35803587, 2001.

26. Loose M, Patient R. Global genetic regulatory networks controllinghematopoietic cell fates. Curr Opin Hematol 13: 229236, 2006.

27. Ma X, Husain T, Peng H, Lin S, Mironenko O, Maun N, Johnson S,Tuck D, Berliner N, Krause DS, Perkins AS. Development of a murinehematopoietic progenitor complementary DNA microarray using a sub-tracted complementary DNA library. Blood 100: 833844, 2002.

28. Majumdar MK, Thiede MA, Haynesworth SE, Bruder SP, GersonSL. Human marrow-derived mesenchymal stem cells (MSCs) expresshematopoietic cytokines and support long-term hematopoiesis when dif-ferentiated toward stromal and osteogenic lineages. J Hematother StemCell Res 9: 841848, 2000.

29. Mendes SC, Robin C, Dzierzak E. Mesenchymal progenitor cells local-ize within hematopoietic sites throughout ontogeny. Development 132:11271136, 2005.

30. Moore KA, Lemischka IR. Stem cells and their niches. Science 311:18801885, 2006.

31. Muller JM, Metzger E, Greschik H, Bosserhoff AK, Mercep L,Buettner R, Schule R. The transcriptional coactivator FHL2 transmitsRho signals from the cell membrane into the nucleus. EMBO J 21:736748, 2002.

32. Ostrowski J, Kawata Y, Schullery DS, Denisenko ON, Higaki Y,Abrass CK, Bomsztyk K. Insulin alters heterogeneous nuclear ribonu-cleoprotein K protein binding to DNA and RNA. Proc Natl Acad Sci USA98: 90449049, 2001.

33. Park IK, He Y, Lin F, Laerum OD, Tian Q, Bumgarner R, Klug CA,Li K, Kuhr C, Doyle MJ, Xie T, Schummer M, Sun Y, Goldsmith A,Clarke MF, Weissman IL, Hood L, Li L. Differential gene expressionprofiling of adult murine hematopoietic stem cells. Blood 99: 488498,2002.

34. Park J, Wood MA, Cole MD. BAF53 forms distinct nuclear complexesand functions as a critical c-Myc-interacting nuclear cofactor for onco-genic transformation. Mol Cell Biol 22: 13071316, 2002.

35. Phinney DG, Hill K, Michelson C, DuTreil M, Hughes C, Humphries

S, Wilkinson R, Baddoo M, Bayly E. Biological activities encoded by themurine mesenchymal stem cell transcriptome provide a basis for theirdevelopmental potential and broad therapeutic efficacy. Stem Cells 24:186198, 2006.

36. Pittenger MF, Mackay AM, Beck SC, Jaiswal RK, Douglas R, MoscaJD, Moorman MA, Simonetti DW, Craig S, Marshak DR. Multilineagepotential of adult human mesenchymal stem cells. Science 284: 143147,1999.

37. Prockop DJ. Marrow stromal cells as stem cells for nonhematopoietictissues. Science 276: 7174, 1997.

38. Ramalho-Santos M, Yoon S, Matsuzaki Y, Mulligan RC, Melton DA.Stemness: transcriptional profiling of embryonic and adult stem cells.Science 298: 597600, 2002.

39. Smyth GK. Linear models and empirical bayes methods for assessingdifferential expression in microarray experiments. Stat Appl Genet Mol

Biol 3: Article 3, 2004.

40. Song L, Webb NE, Song Y, Tuan RS. Identification and functionalanalysis of candidate genes regulating mesenchymal stem cell self-renewaland multipotency. Stem Cells 24: 17071718, 2006.

41. Takizawa H, Kubo-Akashi C, Nobuhisa I, Kwon SM, Iseki M, Taga T,Takatsu K, Takaki S. Enhanced engraftment of hematopoietic stem/progenitor cells by the transient inhibition of an adaptor protein, Lnk.

Blood 107: 29682975, 2006.42. Terskikh AV, Easterday MC, Li L, Hood L, Kornblum HI,

Geschwind DH, Weissman IL. From hematopoiesis to neuropoiesis:evidence of overlapping genetic programs. Proc Natl Acad Sci USA 98:79347939, 2001.

43. Terskikh AV, Miyamoto T, Chang C, Diatchenko L, Weissman IL.Gene expression analysis of purified hematopoietic stem cells and com-mitted progenitors. Blood 102: 94101, 2003.

44. Tsukita S, Yonemura S. Cortical actin organization: lessons from ERM(ezrin/radixin/moesin) proteins. J Biol Chem 274: 3450734510, 1999.




12/12

45. Wei Y, Renard CA, Labalette C, Wu Y, Levy L, Neuveut C, Prieur X,Flajolet M, Prigent S, Buendia MA. Identification of the LIM protein FHL2as a coactivator of beta-catenin. J Biol Chem 278: 51885194, 2003.

46. Wieczorek G, Steinhoff C, Schulz R, Scheller M, Vingron M, RopersHH, Nuber UA. Gene expression profile of mouse bone marrow stromalcells determined by cDNA microarray analysis. Cell Tissue Res 311:227237, 2003.

47. Yang YH, Dudoit S, Luu P, Lin DM, Peng V, Ngai J, Speed TP.Normalization for cDNA microarray data: a robust composite method

addressing single and multiple slide systematic variation. Nucleic AcidsRes 30: e15, 2002.

48. Y in T , L i L . The stem cell niches in bone. J Clin Invest 116:11951201, 2006.

49. Zhou G, Chen J, Lee S, Clark T, Rowley JD, Wang SM. The pattern ofgene expression in human CD34() stem/progenitor cells. Proc Natl AcadSci USA 98: 1396613971, 2001.

50. Zipori D. The stem state: plasticity is essential, whereas self-renewal andhierarchy are optional. Stem Cells 23: 719726, 2005.


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