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OPEN ACCESS ARTICLE
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TISSUE-SPECIFIC STEM CELLS |
aHuffington Center on Aging, Baylor College of Medicine, Houston, Texas, USA;
bUnité de Génétique de la Différenciation, Institut Pasteur, Paris, France;
cUnité des Cytokines et Développement Lymphoïde, Institut Pasteur, Paris, France
Key Words. Hepatic stem cells • Hepatocyte differentiation • Dicarbethoxydihydrocollidine • Cd24a • Notch1
Correspondence: Gretchen J. Darlington, Ph.D., Huffington Center on Aging, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA. Telephone: 713-798-1565; Fax: 713-798-4161; e-mail: gretchen{at}bcm.tmc.edu
Received February 6, 2007;
accepted for publication July 9, 2007.
First published online in STEM CELLS EXPRESS July 19, 2007.
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ABSTRACT |
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 Top Abstract IntroductionMaterials and MethodsResultsDiscussionDisclosure of Potential...AcknowledgmentsReferences |
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Disclosure of potential conflicts of interest is found at the end of this article.
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INTRODUCTION |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionDisclosure of Potential...AcknowledgmentsReferences |
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The present study used untransformed BMEL cell lines. These cells express genes characteristic of both hepatocytes and cholangiocytes and can readily be propagated in an undifferentiated state [23]. When cultured as aggregates, BMEL cells differentiated into hepatocyte-like cells expressing genes characteristic of mature hepatocytes. In contrast, BMEL cells cultured in Matrigel formed mixed cell populations, some of which went on to form ductular structures and express genes characteristic of cholangiocytes and hepatocytes. Importantly, BMEL cells were capable of contributing to new hepatocyte and new cholangiocyte growth after engrafting into damaged livers of the Alb-uPA/severe combined immunodeficient mouse [24, 25]. Engraftment of BMEL cells did not involve cell fusion, a characteristic of hematopoietic stem cell liver engraftment [26], showing that BMEL cells serve as hepatic bipotential progenitor cells in vivo [25]. To identify hepatic progenitor cell surface markers, we analyzed the BMEL cell transcriptome from cells grown in the proliferating (bipotential) and differentiated states. Gene expression analysis was accomplished using Affymetrix (Santa Clara, CA, http://www.affymetrix.com) GeneChip arrays. After identifying differentially expressed genes, Gene Ontology analysis was used to extract potential progenitor cell surface markers from the cohort of genes, which demonstrated a higher relative expression in BMEL cells grown under bipotential conditions compared with expression levels in differentiated, hepatocyte-like BMEL cells.
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MATERIALS AND METHODS |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionDisclosure of Potential...AcknowledgmentsReferences |
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Cell Culture
Culture of BMEL cell lines is described in detail in [23]. Briefly, cells were maintained in RPMI 1640 (Invitrogen, Carlsbad, CA, http://www.invitrogen.com) containing 10% fetal bovine serum, 50 ng/ml epidermal growth factor (EGF), 30 ng/ml insulin-like growth factor-2, 10 µg/ml Insulin, and 50 U of penicillin/streptomycin. Under basal culture conditions, cells were grown on BD BioCoat Collagen I coated flasks (BD Biosciences, San Diego, http://www.bdbiosciences.com). For aggregate cultures, cells approaching confluence were removed from collagen-coated flasks using Trypsin/EDTA (Invitrogen) and resuspended in the above medium. Cell suspensions were then transferred to sterile, uncoated, bacterial 100-mm Petri dishes. Cell aggregates floating in suspension were collected 24 hours (Day 1) and 5 days (Day 5) after transfer to bacterial Petri dishes. Matrigel cultures were done as described in [23].
RNA Isolation
BMEL cells grown under basal, Matrigel, and aggregate conditions were homogenized, and total RNA was extracted using the RNeasy Mini Kit (Qiagen, Hilden, Germany, http://www1.qiagen.com). DNA digestion using RNase-Free DNase (Qiagen) was performed on-column according to the manufacturer's recommendations. RNA was quantified using a NanoDrop ND-1000 Spectrophotometer (NanoDrop, Wilmington, DE, http://www.nanodrop.com). For Affymetrix GeneChip analysis, initial RNA quality was assessed using the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA, http://www.agilent.com) and the NanoDrop ND-1000 Spectrophotometer by the Baylor College of Medicine Microarray Core Facility. In order to be used for GeneChip analysis, RNA had to have an 18S/28S ratio greater than 1.7, a 260/230 ratio greater than 1.5, and a lack of visual RNA degradation on Bioanalyzer electropherograms. All RNA was stored at –80°C until use.
cDNA Synthesis and Reverse Transcription-Polymerase Chain Reaction
Two µg of total RNA isolated from BMEL cells cultured under basal and aggregate conditions was transcribed into cDNA using the SuperScript II RNase H Reverse Transcriptase Kit (Invitrogen). Polymerase chain reaction (PCR) was performed using a 1:20 dilution of sample cDNA, gene-specific primers, and SYBR Green PCR Master Mix (Applied Biosystems, Foster City, CA, http://www.appliedbiosystems.com) according to the manufacturer's protocol. PCR was run using the ABI Prism 7000 Sequence Detection System (Applied Biosystems) as described in [27]. Briefly, thermal cycling conditions consisted of an initial step at 95°C for 10 minutes followed by 40 cycles at 95°C for 15 seconds, 50°C for 60 seconds, and 72°C for 60 seconds. Data analysis was performed using the ABI Prism 7000 SDS Software (Applied Biosystems). Gene-specific PCR primers were designed using Primer Express (Applied Biosystems) and are listed in supplemental online Table 1. In all cases, experiments were done in triplicate. PCR analysis was performed according to a comparative Ct method with the geNorm VBA applet for Microsoft Excel utilizing the method detailed by Vandesompele [28]. The Ct value for each biological replicate represents the average of three technical replicates. β-Actin, 
-tubulin, and 18S were used as the normalizers for this method.
Affymetrix GeneChip Analysis
Gene expression values were determined using Affymetrix moe430a and mouse4302 arrays. The experiment conducted with moe430a arrays consisted of BMEL cell lines 9A1 and 14B3 cultured under basal, Matrigel, and Day 5 aggregate conditions. The experiment conducted with mouse4302 arrays consisted of BMEL cell lines 9A1 and 14B3 cultured under basal, Day 1 aggregate, and Day 5 aggregate conditions. Each cell line/culture condition combination was represented by two biological replicates. The Baylor College of Medicine Microarray Core Facility performed cRNA labeling, GeneChip hybridization, and biotinylated cRNA detection according to standard Affymetrix protocols. Hybridized arrays were scanned using an Affymetrix GeneChip Scanner 3000. The image files were analyzed for probe intensities and converted to tabular formats (CEL files) using the Microarray Suite Expression Analysis software from Affymetrix. Initial GeneChip quality control was done using DNA-Chip Analyzer (Dchip) [29] and the affy [30] and affycoretools analysis packages from the Bioconductor (BioC) [31] project in R [32]. Probe set normalization and expression value calculation were done via the robust multiarray average (RMA) method [33] using the affy BioC package. Prior to statistical analysis for differential probe set expression, the data were filtered to exclude probe sets with low variability by selecting those probe sets whose expression values had an interquartile range (IQR) greater than 0.5. The filtered data were used in unsupervised hierarchical clustering and principal component analysis. Hierarchical clustering was done using a distance measure of 1 minus the Pearson correlation coefficient between samples coupled to complete agglomeration using the R stats package. Principal component analysis was done using the prcomp function from the R stats package. A heat map of gene expression was done with Dchip using Euclidean distance and average linkage options. To compare probe set expression among BMEL culture conditions, we used the linear modeling functions from the BioC limma package [34]. Initially, a linear model was fit to a group-means parameterization design matrix defining the BMEL culture conditions under study. A contrast matrix defining all of the pairwise comparisons was subsequently fit, which utilized an empirical Bayes method to moderate the standard errors of the estimated log-fold changes as described [35]. The F statistic and derived F p values from the second fit combine the pairwise comparisons into a single F test equivalent to a one-way analysis of variance (ANOVA). Controlling the false discovery rate to 0.001 was used to correct for multiple testing across thousands of probe sets. Differentially expressed probe sets were defined as having an fdr corrected F p value less than .001. The resulting list of differentially expressed probe sets was used in downstream Gene Ontology (GO) [36] analysis. GO analysis was accomplished using the hyperGTest function within the BioC GOstats package. Unique Entrez Gene identifiers were evaluated for GO biological process category over representation within a total GO universe defined by BioC mouse4302 annotation. GO categories with a test p value less than .05 and containing at least 20 probe sets are reported in supplemental online Tables 3 and 4.
Protein Isolation
Nonconfluent BMEL cells cultured under basal conditions were detached from collagen-coated flasks by Trypsin/EDTA (Invitrogen) treatment or directly lysed on the dish in RIPA buffer (for Notch analysis). BMEL aggregate cultures were collected by centrifuging culture medium containing cell aggregates at 700 rpm for 5 minutes. For whole cell extracts, BMEL cell pellets or homogenized liver tissue from LPS injected animals were lysed in RIPA Lysis Buffer (Santa Cruz Biotechnology Inc., Santa Cruz, CA, http://www.scbt.com) containing phenylmethylsulfonyl fluoride, sodium orthovanadate, and protease inhibitor cocktail according to manufacturer's protocol. Lysate was centrifuged at 10,000 rpm for 10 minutes at 4°C to remove cellular debris. For nuclear extracts, BMEL cell pellets or homogenized liver tissue from LPS-treated animals were resuspended in hypotonic buffer (10 mM Tris-HCl, pH 7.6, 1.5 mM MgCl2, 10 mM KCl, 0.5 mM dithiothreitol [DTT], and protease inhibitors) and incubated on ice for 5 minutes. Cells were sheared using a 28-gauge needle followed by 10 minutes of incubation on ice. Nuclei were pelleted by centrifugation at 10,000 rpm for 10 minutes at 4°C. The supernatant was collected as the cytoplasmic extract. Nuclei pellets were lysed in a high-salt buffer (20 mM Tris-HCl, pH 7.6, 25% sucrose, 0.42 M NaCl, 1.5 mM MgCl2, 0.2 mM EDTA, 0.5 mM DTT, and protease inhibitors) and incubated on ice for 20 minutes. Extracts were centrifuged at 10,000 rpm for 10 minutes at 4°C. The supernatant was collected as the nuclear extract. Sample protein concentrations were determined using Bio-Rad Protein Assay reagent (Bio-Rad, Hercules, CA, http://www.bio-rad.com). All protein extracts were stored at –80°C until use.
Immunoblot Analysis
Prior to loading polyacrylamide gels, protein extracts were boiled at 100°C for 5 minutes; 50–80 µg of protein extract was separated in 7.5% Tris-HCl Ready Gel Precast Gels (Bio-Rad) and transferred to Immobilon-P nylon membranes (Millipore, Billerica, MA, http://www.millipore.com) or, in the case of Notch detection, to a nitrocellulose membrane (GE Healthcare, Piscataway, NJ, http://www1.gelifesciences.com). Membranes were blocked with 5% nonfat dry milk in 1x Tris-buffered saline/Tween 20 (TBS/T) for 1 hour at room temperature. Primary antibodies were added in 5% nonfat dry milk in 1x TBS/T and incubated overnight at 4°C with the exception of β-actin (1 hour at room temperature). The primary antibodies used were as follows: rabbit anti-mouse Stat5a/b (Santa Cruz Biotechnology; sc-835, 1:100), rabbit anti-human phospho-Stat5a/b (Upstate, Charlottesville, VA, http://www.upstate.com; 05-886, 1:500), rabbit anti-mouse Stat3 (Santa Cruz Biotechnology; sc-482, 1:100), rabbit anti-mouse P-727 Stat3 (Santa Cruz Biotechnology; sc-8001-R, 1:100), goat anti-human Notch1 (Santa Cruz Biotechnology; sc-6014, 1:500), goat anti-human Jag1 (Santa Cruz Biotechnology; sc-6011, 1:500), rabbit anti-human cleaved Notch1 (val1744) (Cell Signaling Technology, Beverly, MA, http://www.cellsignal.com; 2421, 1:2,000), mouse anti-chicken 
-tubulin (MP Biomedicals, Irvine, CA, http://www.mpbio.com; 691251, 1:500), and mouse anti-human β-actin (Sigma; A-5136, 1:5,000). Membranes were then washed 3x10 minutes in 1x TBS/T followed by addition of secondary antibody. The secondary antibodies used were as follows: goat anti-rabbit horseradish peroxidase (HRP) (Jackson Immunoresearch Laboratories, West Grove, PA, http://www.jacksonimmuno.com; 111-035-003, 1:1,000), goat anti-mouse HRP (Santa Cruz Biotechnology; sc-2005, 1:2,000), and swine anti-goat HRP (Caltag Laboratories, Burlingame, CA, http://www.caltag.com; G50007). Membranes were then washed 3x10 minutes in 1x TBS/T followed by specific signal detection using ECL Plus (GE Healthcare) for Notch1, cleaved Notch1, Jag1, and -tubulin. SuperSignal chemiluminescent detection reagents (Pierce, Rockford, IL, http://www.piercenet.com) were used for the remaining antibodies. Treated membranes were exposed to X-OMAT AR film (Kodak, Rochester, NY, http://www.kodak.com) to visualize antibody binding.
Electromobility Shift Assay
Prior to labeling, oligonucleotide probes were gel purified through a 15% polyacrylamide gel electrophoresis gel. Oligonucleotide probes were 3' end-labeled using Klenow and [32P]dCTP (MP Biomedicals) to a specific activity of approximately 1x109 dpm/µg; 100,000 cpm of probe was incubated with 15 µg of whole cell or nuclear extract in binding buffer (100 mM KCl, 25 mM Tris-HCL, pH 7.6, 5 mM DTT, 2 mM MgCl2, and 10% glycerol) with 2 µg of poly(dI-dC) for 30 minutes at room temperature in a 30-µl reaction. Unlabeled competitor oligonucleotide, Stat3 antibody (Santa Cruz Biotechnologies; sc482X), and Stat5a/b antibody (Santa Cruz Biotechnology; sc835X) were incubated for 10 minutes with cell extract on ice prior to addition of labeled probe. Reaction products were visualized by separation on 5% polyacrylamide gels, dried, and exposed to X-OMAT AR film. A mouse intercellular adhesion molecule 1 interferon-gamma-activated site was used to assay for Stat3 binding (5'-AGGAGGTTTCCCGGAAAGTGG-3'). A rat casein beta (Csn2) Stat5 binding site was used to assay for Stat5 binding (5'-GGACTTCTTGGAATTAAGGGA-3').
In Situ Hybridization
Using cDNA generated from cells cultured under basal conditions, DNA riboprobe templates were generated using PCR with Cd24a specific primers (forward: GAAATTCGACGGGATTAAAGGA; reverse: GAACCAAGCCCCCTTTCAG). These primers were designed with extensions at their 5' ends with either T7 or SP6 promoter sequences (T7: GCGTAATACGACTCACTATAGGG; SP6: GCGATTTAGGTGACACTATAG). Digoxigenin labeled RNA riboprobes were generated from DNA riboprobe templates using the Riboprobe Combination kit (Promega, Madison, WI, http://www.promega.com) and Digoxigenin-11-dUTP (Roche Diagnostics, Basel, Switzerland, http://www.roche-applied-science.com). Before use in situ hybridization, labeled RNA riboprobes were diluted in hybridization mix (Ambion, Austin, TX, http://www.ambion.com) to a final concentration of 150–400 ng/ml. Labeled RNA riboprobes were hybridized to fixed adult liver sections by the Baylor College of Medicine In-Situ Core as described in [37].
Immunohistochemistry
Livers from adult animals treated with and without DDC were removed, frozen in Tissue-Tek OCT Compound, and sectioned to a thickness of 5–7 microns. All sections were stored at –80°C until use. Upon use, frozen sections were air-dried and fixed in 100% acetone at 4°C for 10 minutes. Fixed sections were air-dried and washed in 1x phosphate-buffered saline (PBS) for 10 minutes at room temperature (RT). When using biotinylated secondary antibodies, slides were blocked for endogenous biotin using the Avidin/Biotin Blocking Kit (Vector Laboratories, Burlingame, CA, http://www.vectorlabs.com). After washing in 1x PBS, slides were blocked in 20% normal serum diluted in 1x PBS for 1 hour at RT. For the detection of cytokeratin 19 alone, rat anti-mouse monoclonal antibodies (TROMA III clone, a generous gift of Rolf Kemler at the Max-Planck Institute) were incubated at a 1:250 dilution in 1x PBS for 1 hour at RT. Secondary antibodies were either a fluorescein isothiocyanate (FITC) conjugated polyclonal goat anti-rat IgG (Pierce; 31629, 1:50) or a biotinylated polyclonal rabbit anti-rat IgG (Vector Laboratories; BA-4000, 1:50). Biotinylated antibodies were detected using Texas Red Avidin D (Vector Laboratories; A1100, 1:50) for 30 minutes at RT. For double Cd24a and cytokeratin 19 immunostaining, a rat anti-mouse Cd24a antibody (BD Biosciences; 557436, 1:50) was incubated with sections overnight at 4°C. Cd24a antibody was detected using a biotinylated mouse anti-rat IgG2b specific antibody (Serotec Ltd., Oxford, U.K., http://www.serotec.com; MCA1294B, 1:50) for 1 hour at RT followed by Texas Red Avidin D (A1100, 1:50) for 30 minutes at RT. Cytokeratin 19 was subsequently detected using primary antibody as described above coupled with a FITC conjugated mouse anti-rat IgG2a specific antibody (Serotec; MCA278F, 1:50) for 1 hour at RT. For double Cd24a and Cd45 immunostaining, a FITC conjugated rat-anti-mouse Cd24a antibody (BD Biosciences; 553261, 1:50) was incubated with sections for 1 hour at RT. Cd45 was subsequently detected using a phycoerythrin (PE) conjugated rat anti-mouse Cd45 antibody (BD Biosciences; 553081, 1:50) incubated for 1 hour at RT. All images were captured using a Hamamatsu C5810 color chilled 3ccd camera (Hamamatsu Photonics, Hamamatsu City, Japan, http://www.hamamatsu.com) and an Olympus IX70 microscope (Olympus, Tokyo, http://www.olympus-global.com).
Fluorescence-Activated Cell Sorting
Untreated and DDC-treated adult mouse livers were perfused with 0.28 mg/ml collagenase IV (Sigma; C-5138). Cells were passed through a 70-µm filter to remove undigested tissue debris and centrifuged at 10g for 5 minutes to pellet hepatocytes. The supernatant was centrifuged at 350g for10 minutes and resuspended in 90 µl of running buffer (1x PBS, pH 7.2, 2 mM EDTA, 2% bovine serum albumin) per 107 total cells. Resuspended cells were mixed with 10 µl of anti-mouse Ter119 microbeads (Miltenyi Biotec, Bergisch Gladbach, Germany, http://www.miltenyibiotec.com; 130-049-901) per 107 total cells and incubated at 4°C for 15 minutes. The labeled cell suspension was applied to an autoMACS separator (Miltenyi Biotec) to deplete Ter119 positive cells. The depleted cell suspension was then incubated with fluorescently conjugated antibodies on ice for 10 minutes followed by resuspension to 107 cells per milliliter for fluorescence-activated cell sorting (FACS) analysis. Data were acquired using a Dako (Glostrup, Denmark, http://www.dako.com) Cytometer. The antibodies used for FACS analysis were FITC-conjugated rat anti-mouse CD45 monoclonal antibody (mAb) (BD Biosciences; 553080), FITC-conjugated rat anti-mouse Ter119 (BD Biosciences; 557915), and PE-conjugated rat anti-mouse CD24 mAb (BD Biosciences; 553262).
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RESULTS |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionDisclosure of Potential...AcknowledgmentsReferences |
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Differentially Expressed Genes in Undifferentiated (Basal) Versus Hepatocyte-Like (Aggregate) Culture Conditions
Cells were analyzed 5 days after aggregation (Day 5 [D5] aggregate) to characterize the gene expression profile of hepatocyte-like cells in relation to undifferentiated BMEL cells as initially studied by Strick-Marchand et al. [23]. To put the hepatocyte-like gene expression profile into context, gene expression changes occurring earlier after BMEL cell aggregation were also investigated. An earlier time point was added, and cells were analyzed 24 hours (Day 1 [D1] aggregate) after aggregation. These samples were hybridized to Affymetrix mouse4302 GeneChips, which approximately doubled the number of probe sets available for analysis. As before, RMA normalization and model expression, IQR expression filtering, and PCA were used to visualize the relationship among the culture conditions. As with the moe430a experiment, the first three principal components accounted for the majority of the total variance. Graphing the first two principal components against each other revealed that PC1, at 62% of the total variance, primarily defined the difference among the three BMEL cell culture conditions: basal, D1 aggregate, and D5 aggregate (data not shown). PC2 again defined the small variance among biological replicates of the 9A1 and 14B3 cell lines in each culture condition (data not shown).
Differential probe set expression was determined using a linear model fit to a group-means parameterization design matrix defining the basal, D1, and D5 culture conditions. In this model, samples from both cell lines within each culture condition were grouped and treated as four biological replicates due to the low contribution of the cell line effect to the total variance. A contrast matrix detailing all the pairwise culture condition comparisons (D5 vs. basal, D1 vs. basal, and D5 vs. D1) was used in a second fit to extract log2 fold changes among culture conditions. ANOVA F p values from the second fit were corrected for multiple testing by controlling the false discovery rate [38]. Probe sets with an adjusted F p value of less than .001 were considered to be significantly changing across culture conditions and were included in further analysis. In this way, probe sets not contributing information about the difference between basal and aggregate samples were removed; 34 genes (supplemental online Table 1) were selected for PCR validation of the array-determined fold changes. These genes showed a broad range of fold changes varying from strongly upregulated in basal samples to strongly upregulated in aggregate samples to no change among culture conditions. Each of the 34 genes was assayed in basal, D1, and D5 samples. Figure 2 shows array and PCR determined log2 fold changes between the aggregate and basal samples plotted against each other. A least squares best-fit line had an r2 value of .71, indicating good agreement among fold changes determined by the array experiment and PCR. Figure 2 also shows that the array data underestimate biological fold change as determined by PCR, reflecting the greater accuracy of PCR versus array detection [39].
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Gene Ontology "Transcription" Analysis
We also utilized GO annotation of the significantly changing probe sets to identify factors responsible for driving differentiation of BMEL cells and factors responsible for maintaining undifferentiated BMEL cells. We looked specifically at GO biological processes containing the word "transcription," which include transcription factors (TFs) and factors regulating the transcriptional process.
We knew from GO biological process over-representation analysis that probe sets from groups A, B, and C of Figure 3 contributed to many aspects of liver function. The largest group of TFs influencing hepatocyte function came from within group A, those probe sets strongly induced by D5 of BMEL cell aggregation. Nr1i3 (Car), Nr1i2 (Pxr), Nr5a2 (Lrh), Hnf4g, Nfe2l2 (Nrf2), and Mlxipl (Wbscr14, ChREBP) were all highly expressed by D5 of aggregation. These genes are involved in the induction of bile acid synthesis [41], xenobiotic gene induction [42–44], lipid synthesis [45], and carbohydrate metabolism [46], all of which are normal liver functions.
Within groups B and C, 24 hours after aggregation, we detected the modest induction of the TF Stat3, known to be critical for the liver acute phase response [47] and the transient induction of Stat5. Because Stat proteins are involved in many aspects of the acute phase response, and evidence exists that Stat3 is activated in rat oval cells [48], reverse transcription-PCR analysis was used to confirm Stat3 and Stat5 expression levels. A slight trend for higher expression in aggregate cultures was revealed, which did not reach statistical significance (supplemental online Table 1). Figure 4 shows Western analysis of Stat3 and Stat5 protein expression and phosphorylation. The second and fourth panels of Figure 4A show that both total Stat5 and total Stat3 protein expression did not change between basal, D1, and D5 samples. However, Stat3 seemed to be constitutively phosphorylated across culture conditions (Fig. 4A, panel 3), whereas little if any Stat5 phosphorylation was detected (Fig. 4A, panel 1). Stat3 is known to be a target of EGF in the liver; therefore, the use of EGF during BMEL cell culture could be contributing to constitutive Stat3 phosphorylation across basal and aggregate culture conditions. Figure 4B serves as a control for this Western blot and shows that the Stat3 and Stat5 bands detected in basal samples are the same size as bands expressed in adult livers before and after 1 hour of LPS treatment, which is known to induce the expression and phosphorylation of Stat proteins [49]. Electrophoretic mobility shift assay (EMSA) analysis of BMEL protein extracts did not detect any specific Stat5 or Stat3 binding to DNA consensus elements despite phosphorylation and apparent activation of Stat3 (Fig. 5).
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Gene Ontology Cellular Component Analysis
A main goal of this analysis was to detect cell surface markers for purification of hepatic progenitor cells from the adult liver. Best candidates would be genes whose expression is higher in basal cultures relative to aggregate cultures. Of the 2,656 genes (supplemental online Table 2) shown to be differentially expressed, genes associated with the cell surface or the extracellular space were filtered based on GO cellular component terms "integral," "plasma membrane," or "extracellular" in their GO descriptions. Using D5 of aggregation as an approximate filter for genes expressed by hepatocytes, we eliminated probe sets not displaying at least a twofold greater expression in basal cultures from the D5 versus basal array contrast. This reduced our chances of selecting markers with a significant level of expression in hepatocytes. The list of cell surface markers can be found in supplemental online Table 5. It is encouraging that the TWEAK receptor, Tnfrsf12a, was identified as a cell surface progenitor cell candidate. Recently, Jakubowski et al. showed that mice null for Tnfsf12 fail to undergo a ductular reaction and oval cell proliferation in response to DDC treatment [58]. Upregulation of Tnfrsf12a in undifferentiated BMEL samples could indicate that these cells use signaling mechanisms similar to oval cells, further supporting the use of the BMEL cells as an experimental model. Using PCR, the expression of candidates Cmkor1, Vcam1, Fzd2, Fzd6, Epha4, Cd24a, Steap1, Cd9, and Gja1 was confirmed to be higher in basal samples than aggregate samples (supplemental online Table 1). In addition, PCR confirmed Cmkor1, Steap1, and Gja1 were higher in basal samples relative to D1 aggregate samples. It was not surprising that some of the markers are still expressed in BMEL cells after 24 hours of aggregation. D1 of aggregation probably represents a transition from bipotential, undifferentiated cells to differentiated, hepatocyte-like cells and for this reason might display gene expression patterns of both stages.
To validate expression of our candidate cell surface markers in adult mouse liver, we used a chemical model of liver injury that causes oval cell proliferation [22, 59]. Treatment with the porphyrinogenic agent DDC causes an atypical ductular proliferation in which progenitor cells (oval cells) emanate from terminal bile ductules known as the canals of Herring [1]. We determined which BMEL cell-derived candidate genes are expressed within the expanded progenitor/oval cell compartment after 3 weeks of DDC treatment while remaining absent from surrounding cell types. Figure 7A shows the effects of 3 weeks of DDC treatment on mouse liver. Ductular proliferation was readily apparent with routine H&E staining. In addition to progenitor cell proliferation and expansion, a significant inflammatory infiltration characteristic of all models of oval cell induction was observed [60]. Figure 7B shows cytokeratin 19, a bile epithelial and progenitor cell marker, staining in an untreated mouse liver highlighting the bile ducts. Compared with staining in Figure 7B, Figure 7C shows the expansion of cytokeratin 19 stained areas, marking the extent of ductular expansion and oval cell proliferation. Figure 7D–7F shows RNA localization of the candidate marker Cd24a using in situ hybridization. Cd24a, also known as the heat stable antigen, is a glycosylated GPI linked cell surface protein upregulated in basal samples (supplemental online Tables 1, 2). Arrows point to regions of digoxigenin-labeled antisense probe/antibody precipitate at both low (Fig. 7E) and higher magnification (Fig. 7F) showing Cd24a mRNA localizing to cells surrounding bile ducts. The remainder of Figure 7 shows the localization of Cd24a protein in the DDC induced model of oval cell proliferation. Cytokeratin 19 was used as a general marker for progenitor cells, and the pan-hematopoietic marker Cd45 was used to label the DDC associated inflammatory cells. Figure panels 7G and 7H depict cytokeratin 19 and Cd24a immunostaining, respectively, in DDC treated animals. The merged image of these two micrographs (Fig. 7I) shows that the vast majority of the DDC induced ductular reaction that is positive for cytokeratin 19 protein is also positive for Cd24a protein. No clear Cd24a staining is visible in the surrounding parenchyma indicating that little if any Cd24a is expressed on hepatocytes. Figure 7J–7L offers a higher magnification image of cytokeratin 19 and Cd24a colocalization at sites of ductular proliferation. Although Cd24a immunostaining colocalizes with most regions positive for cytokeratin 19 (Fig. 7L), asterisks depict small regions of Cd24a immunostaining with little or no cytokeratin 19 colocalization. Because DDC treatment caused inflammation in and around the same areas where ductular proliferation and Cd24a staining are seen, we tested to see whether Cd24a positive cells were also Cd45 positive. If Cd24a and Cd45 colocalize it would indicate that the Cd24a positive cells may be of hematopoietic origin and therefore not hepatic progenitor cells. Figure panels 7M and 7N illustrate Cd24a and Cd45 immunostaining in and around a region of ductular proliferation. The merge of these photomicrographs (Fig. 7O) clearly shows that these two markers do not overlap, indicating that Cd24a positive cells are not derived from the DDC-induced inflammatory reaction. Consistent with the increase in immunostaining of Cd24a in livers from DDC-treated animals, FACS analysis (supplemental online Fig. 1) of livers from DDC-treated animals shows a 4.2-fold increase in Cd24a positive cells when compared with livers from untreated animals.
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DISCUSSION |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionDisclosure of Potential...AcknowledgmentsReferences |
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As a model for liver progenitor cell gene expression, we studied two independently isolated BMEL cell lines known to contribute to both hepatocyte and cholangiocyte repopulation of damaged livers following transplantation. Principal component analysis of microarray expression data revealed little mRNA expression variation between the two independent BMEL cell lines, demonstrating the reproducibility of phenotypic profiles of BMEL cell lines isolated following the "plate and wait" isolation procedure. This reproducibility makes this isolation technique ideally suited for the production of liver progenitor cell lines as it enables reliable comparison between samples. PCA analysis and hierarchical clustering of unsupervised BMEL gene expression highlighted a clear distinction between cells differentiated in aggregate or Matrigel cultures and undifferentiated and heritably bipotential cells maintained in basal cultures. We have exploited this differential response of BMEL cells to culture condition to identify molecules showing enriched expression in liver progenitor cells and to search for regulatory pathways potentially involved in maintenance of their bipotentiality.
To define the initial gene expression changes occurring during differentiation, we examined two contrasts. The first was the difference between 24-hour aggregate and basal cultures to reveal genes involved in early actions of aggregate-induced differentiation as well as those genes uniquely expressed in undifferentiated bipotential cells. The second contrast was the comparison between D5 aggregate and basal growth conditions to eliminate those genes expressed by hepatocytes.
Five main expression profile groups (A–E; Fig. 3) were identified that ranged from genes highly expressed in basal cultures to genes highly expressed in aggregate cultures. Gene Ontology analysis of these groups revealed a dramatic switch in functional profile as proliferating BMEL cells differentiated into hepatocyte-like cells. This analysis revealed that basal culture conditions, while maintaining bipotentiality, result in the active proliferation of BMEL cells and that aggregating culture conditions induce a mature liver differentiation program resulting in repression of cell cycle associated genes and induction of many genes characteristic of liver metabolism.
In addition to cell surface markers, we also wanted to identify transcription factors maintaining bipotentiality of BMEL cells as well as factors involved in early induction of hepatocyte specification. We identified not only transcription factors but also genes that regulate transcriptional processes. Three transcription factors (Stat3, Stat5, and Notch1) were chosen for further analysis due to their known importance for liver function. EMSA analysis of both Stat3 and Stat5 failed to reveal any binding to their respective consensus response elements within extracts of BMEL cells cultured under basal, D1 aggregate, or D5 aggregate conditions. This was surprising for Stat3 due to its high level of phosphorylation in all samples, indicating an apparent active state. However, another mechanism might be at play for Stat3. A study by De Miguel et al. showed that Stat3 has the ability to act as a coregulator for the steroid receptors Ar, Esr1, Nr3c1 (Gr), and Nr3c2 (Mr) [61]. According to microarray expression data, both Nr3c1 and Nr3c2 are expressed by BMEL cells, and, even though they were not differentially regulated across culture conditions (data not shown), availability of a coregulator could be limiting.
In murine fetal liver, Jagged1 is expressed in cells surrounding vessels, whereas Notch1 is expressed in all cells [62]. In the adult liver, Jagged1, Notch1, and the activated cytoplasmic domain of Notch, NICD, are all present in hepatocytes and bile duct cells. Partial hepatectomy, which causes proliferation of hepatocytes, is accompanied by an increase in NICD [63]. In BMEL cells, the activated Notch1 peptide NICD was present under basal conditions and not under aggregate conditions. In addition, array analysis indicated that both Numb and Sel1h, two Notch signaling pathway inhibitors, were upregulated after 5 days of aggregation (supplemental online Table 2) [64, 65]. This pattern of Notch1 activation in undifferentiated BMEL cells is consistent with findings by Tanimizu et al., which showed that Notch was expressed in hepatoblasts and that active Notch signaling blocked differentiation into hepatocytes [66]. BMEL cells grown under basal conditions may utilize Notch cell/cell signaling to maintain a niche required for the undifferentiated and bipotential states. Upon differentiation/aggregation, induction of Numb and/or Sel1h may play a role in shutting down Notch signaling in differentiating BMEL cells.
Candidate progenitor cell surface genes were identified by filtering the 2,656 probe sets displaying significant differential expression for Gene Ontology terms associated with membrane localization and/or the extracellular space. From the basal versus D5 contrast, 64 genes were identified as having enriched expression in undifferentiated BMEL cells. In situ hybridization analysis showed Cd24a to be a promising cell surface candidate. In adult mouse livers, Cd24a mRNA was localized to cells surrounding bile ducts, the putative resting niche for adult liver progenitor cells. Immunofluorescent localization of Cd24a in DDC-treated livers showed the protein to localize to the oval cell compartment within regions of ductular proliferation and to bile epithelial cells within the same region. No Cd24a protein was detected on hepatocytes. From studies in other organisms, there is evidence that Cd24a may play a role in progenitor cells. For example, it has been shown that mammary fat pad repopulation capacity segregates with epithelial cells showing Cd24a low expression [67]. In addition, Cd24a was identified as a potential marker for renal progenitor cells in an array study of embryonic and adult kidney [68]. Recent evidence has also suggested that Cd24a may serve as a prognostic marker for intrahepatic cholangiocarcinoma [69]. Liver cancer is one of many cancers thought to be a result of aberrant progenitor cell proliferation [70]. Double labeling with Cd45 and Cd24a antibodies showed these two markers to be mutually exclusive, indicating that cells expressing Cd24a are not of hematopoietic origin. In addition, FACS analysis of DDC-treated livers demonstrated that the Cd24a epitope remains intact after collagenase perfusion, indicating that the Cd24a antibody used in this study can be effectively used to isolate cells. Consequently, we conclude that Cd24a represents a genuine candidate cell surface marker for liver-derived progenitor cells.
When stem cells are rare, immortalized cell lines that undergo differentiation in vitro may serve to identify novel genes that can be subsequently verified in vivo for their utility. BMEL cells represent such a model system, and the data presented here have shown Cd24a to be a promising cell surface candidate for the isolation of progenitors from adult liver.
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= D1 versus basal contrast; 
= D5 versus basal contrast. Abbreviations: B, basal; D1, day 1; D5, day 5; FC, fold change; PCR, polymerase chain reaction.
