Stem Cells International

Stem Cells International / 2016 / Article
Special Issue

Towards Creating the Perfect In Vitro Cell Model

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Research Article | Open Access

Volume 2016 |Article ID 8648356 | 22 pages | https://doi.org/10.1155/2016/8648356

Highly Synchronized Expression of Lineage-Specific Genes during In Vitro Hepatic Differentiation of Human Pluripotent Stem Cell Lines

Academic Editor: Renke Li
Received31 Jul 2015
Accepted01 Dec 2015
Published01 Feb 2016

Abstract

Human pluripotent stem cells- (hPSCs-) derived hepatocytes have the potential to replace many hepatic models in drug discovery and provide a cell source for regenerative medicine applications. However, the generation of fully functional hPSC-derived hepatocytes is still a challenge. Towards gaining better understanding of the differentiation and maturation process, we employed a standardized protocol to differentiate six hPSC lines into hepatocytes and investigated the synchronicity of the hPSC lines by applying RT-qPCR to assess the expression of lineage-specific genes (OCT4, NANOG, T, SOX17, CXCR4, CER1, HHEX, TBX3, PROX1, HNF6, AFP, HNF4a, KRT18, ALB, AAT, and CYP3A4) which serve as markers for different stages during liver development. The data was evaluated using correlation and clustering analysis, demonstrating that the expression of these markers is highly synchronized and correlated well across all cell lines. The analysis also revealed a distribution of the markers in groups reflecting the developmental stages of hepatocytes. Functional analysis of the differentiated cells further confirmed their hepatic phenotype. Taken together, these results demonstrate, on the molecular level, the highly synchronized differentiation pattern across multiple hPSC lines. Moreover, this study provides additional understanding for future efforts to improve the functionality of hPSC-derived hepatocytes and thereby increase the value of related models.

1. Introduction

The generation of a clinically relevant in vitro hepatocyte experimental model is challenging since the model has to mirror the diverse properties and functionality of its in vivo counterpart [1]. At present, primary cells isolated from human livers are considered to be the best in vitro hepatocyte model [2]. However, these cells still have several limitations, such as shortage in availability, rapid phenotypical changes following their isolation, and in vitro manipulation including decreased hepatic enzyme functionality, short life span, substantial interindividual variations, and lack of bile collection [24]. Thus, the pursuit of a better candidate model is strongly motivated. In this regard, human pluripotent stem cells (hPSCs), characterized by their unique capacities of self-renewal and differentiation, may provide an attractive alternative. These cells constitute an excellent human cell source for use in basic research and drug discovery and also potentially in future regenerative medicine and cell therapy applications. Moreover, the use of human induced pluripotent stem cells (hiPSCs), which are stem cells derived from reprogrammed somatic cells, enables the development of disease models and studies of interindividual diversity in safety pharmacology and toxicology [5, 6]. However, in order to fully realize the great potential of these cells, robust differentiation protocols are required to ensure reproducibility and recapitulation of the mature hepatic functionality in the final cell population [7]. Recent reports have indeed demonstrated efficient differentiation of hPSCs into hepatocytes that share many features of their in vivo counterparts, including the expression of hepatic markers and genes involved in drug metabolism and transport [811]. In addition, the cells have shown the ability to accurately predict and classify the toxicity of various compounds [6, 12].

Although the results from the hPSC-differentiation are encouraging, establishment of in vivo-like functionality of the in vitro-derived hepatocytes has still not been achieved, mainly due to impaired expression of key genes, which are critical for the metabolic functionality of the cells, a limitation that inhibits their utility in some applications in therapeutics and drug discovery [5]. Recently, Asplund and coworkers reported a standardized protocol to generate homogenous hepatocyte-like cell cultures from panel hPSC lines, which displayed metabolic diversity reminiscent of intraindividual variation found in the human population. That study showed notable similarities between the large number of cell lines analyzed but also variability of hepatic enzyme activity including CYP1A, CYP2C9, CYP2D6, and CYP3A [13]. The majority of previously reported protocols for differentiating hPSCs to hepatocyte-like cells recapitulate liver development, where the cells are first differentiated to definitive endoderm (DE) and subsequently to hepatoblast (the hepatic progenitor that gives rise to both hepatocytes and biliary cells) and finally to hepatocyte-like cells [7, 1315]. The growth and differentiation of hepatocytes during embryonic liver organogenesis is known to be highly synchronized [16]. However, whether biological replicates from multiple hPSC lines are synchronized through an in vitro hepatocyte differentiation process has not been thoroughly investigated. Synchronicity accounts for the robustness of the differentiation protocol in recapitulating liver organogenesis in vitro, and thus the onset time of the different developmental stages for biological replicates should be consistent.

In this study, we have investigated the expression of a selected set of lineage-specific genes during the differentiation of six hPSC lines, including three hESC and three hiPSC lines, to hepatocyte-like cells applying a protocol further developed from the procedure reported by Asplund and coworkers [13]. Sixteen key genes were analyzed by reverse transcription quantitative real-time PCR (RT-qPCR): OCT4 and NANOG as pluripotent markers; T (Brachyury) as primitive streak marker; CXCR4, SOX17, and CER1 as definitive endoderm markers; HHEX as ventral foregut endoderm marker [17]; PROX1, TBX3, and HNF6 as hepatoblast markers; AFP as fetal hepatocyte marker; and HNF4A (HNF4a), CYP3A4, SERPINA1 (AAT), ALB (albumin), and KRT18 (CK18) as hepatic markers [14]. The RT-qPCR results were statistically analyzed using Spearman’s rank correlation. A clustering analysis was also performed based on the gene expression values. The results presented here show highly synchronized and correlated gene expression profiles across the six cell lines. In addition, the functionality of mature hepatocytes-like cells was confirmed by measuring the drug metabolizing activity of Cytochrome P450 (CYP) enzymes CYP1A, CYP3A, CYP2C9, CYP2D6, and CYP2C19. Furthermore, these cells have the ability to store glycogen and they express the drug transporters MRP2, OATP1B1, NTCP, and BSEP. Interestingly, the hESC or hiPSC lines did not show any pattern indicating any specific correlation to each other. Furthermore, the clustering analysis shows the distribution of lineage-specific markers in groups, reflecting the differentiation stages of hepatocytes.

2. Materials and Methods

2.1. Human Pluripotent Stem Cell Culture and Differentiation

All hPSC lines used in this study are XY and were provided by Takara Clontech (http://www.clontech.com). The cells were thawed, maintained, and passaged in the feeder-free Cellartis DEF-CS culturing system (Takara Clontech) according to the manufacturer’s recommendations. The cell lines were used in subsequent differentiation experiments at the following passages: Cellartis SA121 p.10, Cellartis SA181 p.11, Cellartis ChiPSC6b p.16, Cellartis AS034 p.10, Cellartis P11012 p.18, and Cellartis P11025 p.21. (Throughout this paper, the cell lines are referred to with their short names: SA121, SA181, ChiPSC6b, AS034, P11012, and P11025, resp.).

The hPSCs were differentiated into definitive endoderm (DE) cells by applying Cellartis DE differentiation kit (Takara Clontech) according to the manufacturer’s recommendations.

At day 7, the cells were harvested according to the manufacturer’s recommendations and differentiated into hepatocyte-like cells applying a prototype of the Cellartis Hep differentiation kit (available upon request from Takara Clontech) as illustrated in Figure 1.

2.2. RNA Extraction and Real-Time Quantitative Polymerase Chain Reaction

Cell samples were collected daily before performing medium change (if medium change was scheduled) during the differentiation process and preserved in RNAprotect Cell Reagent (Cat. number 76526, QIAGEN) at −20°C. RNA was extracted using MagMAX-96 Total RNA Isolation Kit (Cat. number AM1830, Life Technologies) and quantified by using GeneQuantpro spectrophotometer. Eighty ng RNA of each sample was used to synthesize cDNA applying the iScript cDNA Synthesis Kit (Cat. number 170-8890, BIO-RAD).

TaqMan Fast Advanced Master Mix (Cat. number 4444557, Life Technologies) and TaqMan Gene Expression Assays were used in RT-qPCR. Table 1 summarizes the assays that were used and on which days they were applied. Each reaction included 1.6 ng cDNA and was run in duplicate. CREBBP was used as reference gene and an in-house calibrator was used for sample normalization as well [13]. For hepatoblast, fetal, and mature hepatocytes markers an RNA pool of freshly isolated human primary hepatocytes from 5 different donors was used as a calibrator. Interplate controls were added for plate normalization.


Gene symbol Product number Days

ABCB11 (BSEP)Hs00184824_m131, 34
ABCC2 (MRP2)Hs00960494_m131, 34
AFPHs00173490_m110–35
ALBHs00910225_m119–35
T (Brachyury)Hs00610080_m10–3
CER1Hs00193796_m11–9
CREBBPHs00231733_m10–35
CXCR4Hs00237052_m12–10
CYP3A4Hs00604506_m121–35
HHEXHs00242160_m11–11
HNF4AHs00230853_m19–35
ONECUT1 (HNF6)Hs00413554_m110–35
KRT18Hs02827483_g113–35
KRT19Hs00761767_s16–35
NANOGHS2387400_g10–7
OCT4Hs04260367_gH0–7
PROX1Hs00896294_m114–35
SERPINA1 (AAT)Hs00165475_m119–35
SLCD1B1 (OATP1B1)Hs00272374_m131, 34
SLC10A1 (NTCP)Hs00161820_m131, 34
SOX17Hs00751752_s12–10
TBX3Hs00195621_m17–35

The difference in quantification cycle () and relative quantification (RQ) were calculated according to the following formulas:

2.3. Statistical Analysis of Gene Expression Data

For each gene, the expression data consisted of a matrix of RQ values, where represents the six cell lines and represents the days at which expression was measured for the particular gene. For each gene, the RQ vectors of every pair of cell lines were tested for association using Spearman rank correlation, which is a nonparametric test, not sensitive to extreme values, which can be used to detect nonlinear relationships [18]. Correlation coefficients were interpreted according to a scale where 0.8–1.0 was defined as “very strong,” 0.6–0.8 as “strong,” 0.4–0.6 as “moderate,” 0.2–0.4 as “weak,” and 0.0–0.2 as “very weak” or “no correlation.”

For the clustering analysis, the matrix was replaced with the vector median (), where each value is the median RQ for a particular day over all six cell lines. Groups of these RQ vectors, representing different combinations of genes, were hierarchically clustered with the HCL algorithm in the MultiExperiment Viewer software v4.9 (http://www.tm4.org/mev.html), using Spearman rank correlation as similarity metric and complete linkage as the linkage rule.

2.4. Immunocytochemistry

At days 0, 5, 7, 14, 24, 25, 29, and 30 of differentiation, the cells were washed with DPBS (+/+) (Cat. number 14040-, Life Technologies) and fixed by incubation for 10 min in 4% formaldehyde (Cat. number 02176, Histolab, Västra Frölunda, Sweden) and then washed and maintained in DPBS (+/+) until processing. TNB-blocking buffer was prepared by mixing 0.1 M Tris (Cat. number 10421-1, Kebo Lab AB) adjusted with hydrochloric acid 36.5%–38% (Cat. number H1758, Sigma) to pH 7.5 with 0.15 M NaCl (Cat. number S5886, Sigma) in dH2O. Blocking reagent from Perkin Elmer TSA-kit (Cat. number FP1012, Perkin Elmer) was slowly added to Tris-HCl/NaCl buffer under stirring to final concentration of 0.5%; then the solution was heated to 60°C until the blocking reagent was dissolved. The cells were washed once with DPBS (+/+), followed by incubation for 10 min in 0.3% Triton-X (Cat. number T8532, Sigma) in DPBS (+/+), and the cells were subsequently incubated in TNB-blocking buffer for 1 h. Primary antibodies diluted in 0.1% Triton-X in DPBS (+/+) were added to the cultures and incubated over night at 4°C. The following day, the cells were washed three times with DPBS (+/+); then the secondary antibodies and DAPI diluted in 0.1% Triton-X in DPBS (+/+) were added and the cells were incubated for 2 h at RT. Finally, the cells were washed three times with DPBS (+/+) before being imaged in a fluorescence microscope and photographed. The photos were processed using ImageJ software (http://imagej.nih.gov/ij/). Table 2 summarizes the different primary and secondary antibodies applied, the dilution ratios, and the days at which respective markers were analyzed.


Primary antibodyClassDilutionDistributor,
catalogue number
Secondary antibodyDilutionDistributor, catalogue numberApplied to cells day

Albumin (ALB)Rabbit-IgG1 : 500DakoCytomation, A0001Donkey anti-rabbit-IgG-Alexa 4881 : 1000ThermoFisher Scientific, A-2120624, 25, 29, 30
CYP3A (4)Rabbit-IgG 1 : 200Cypex, PAP011Donkey anti-rabbit-IgG-Alexa 4881 : 1000ThermoFisher Scientific, A-2120629, 31
CK 18 Mouse-IgG11 : 100DakoCytomation, M7010Goat anti-mouse-IgG-Alexa 4881 : 500ThermoFisher Scientific, A-1102924, 25, 29, 30
HNF4aRabbit-IgG1 : 400Santa Cruz, sc-8987Donkey anti-rabbit-IgG-Alexa 4881 : 1000ThermoFisher Scientific, A-2120614, 24, 25, 29, 30
Oct4Mouse-IgG2b1 : 200Santa Cruz, sc-5279Donkey anti-mouse-IgG-Alexa-4881 : 1000ThermoFisher Scientific, A-212020, 5, 7
Sox17Goat-IgG1 : 500R&D Systems, AF1924Donkey anti-goat-IgG Alexa 5941 : 1000ThermoFisher Scientific, A-110585, 7
SSEA-1Mouse-IgM1 : 200Santa Cruz, sc-21702Donkey anti-mouse-IgG-Alexa-4881 : 1000ThermoFisher Scientific, A-212020
AATRabbit-IgG 1 : 200DakoCytomation, A0012Donkey anti-rabbit-IgG-Alexa 4881 : 1000ThermoFisher Scientific, A-2120624, 25, 29, 30
α-fetoprotein (AFP)Mouse-IgG1 1 : 500Santa Cruz, sc-51506Goat anti-mouse-IgG-Alexa 5941 : 1000ThermoFisher Scientific, A-1103214, 24, 25, 29, 30
BSEPGoat-IgG1 : 100Santa Cruz, sc-17292Donkey anti-goat-IgG-Alexa-4881 : 1000ThermoFisher Scientific, A-1105529
OATP-C (OATP1B1)Rabbit-IgG1 : 200Santa Cruz, sc-33609Donkey anti-rabbit-IgG-Alexa 4881 : 1000ThermoFisher Scientific, A-2120629
NTCPGoat-IgG1 : 400Santa Cruz, sc-107030Donkey anti-goat-IgG-Alexa-5941 : 1000ThermoFisher Scientific, A-1105829
MRP2Rabbit-IgG1 : 50Santa Cruz, sc-20766Donkey anti-rabbit-IgG-Alexa 4881 : 1000ThermoFisher Scientific, A-2120629

2.5. Cytochrome P450 (CYP) Enzymes Activity Assay

The activities of the enzymes CYP1A, CYP3A, CYP2C9, CYP2C19, and CYP2D6 in hepatocyte-like cells differentiated from all hPSC lines used in this study and in cryoplateable human primary hepatocytes from four different donors (BioreclamationIVT, Frankfurt am Main, Germany) were measured as described previously with small modification [13]. Briefly, hPSC-derived hepatocyte-like cells at day 29 of the hepatic differentiation and primary human hepatocytes (cultured for in total 20 h after plating) were incubated in a cocktail of CYP substrates, 10 μM phenacetin a CYP1A substrate, 10 μM bufuralol a CYP2D6 substrate, 10 μM diclofenac a substrate of CYP2C9, 50 μM mephenytoin a substrate of CYP2C19, and 5 μM midazolam a substrate of CYP3A. The formation of the metabolites (paracetamol (CYP1A), 1-OH-bufuralol (CYP2D6), 4-OH-diclofenac (CYP2C9), 4-OH-mephenytoin (CYP2C19), and 3-OH-midazolam (CYP3A)) was determined by liquid chromatography/mass spectrometry (LC/MS) performed at Pharmacelsus GmbH (Saarbrücken, Germany). The samples were collected in duplicate for each cell line, and the metabolite concentration was normalized to the protein amount per well and incubation time and the results are presented as pmol metabolite/mg protein/min.

2.6. PAS Staining

The cells were fixed as described above. A PAS kit was applied (395B-1KT, Sigma Aldrich), in which the cells were incubated in periodic acid for 15 min on a shaker at RT. Then the cells were washed with dH2O and incubated in SCHIFF reagent for 30 min on a shaker at RT. Subsequently the cells were washed with dH2O and incubated in hematoxylin for 90 seconds and finally the cells were washed with dH2O again.

3. Results

3.1. Human PSC Culturing and Hepatic Differentiation

Human PSCs cultured in the Cellartis DEF-CS culturing system showed typical stem cell morphology (round cells with big nucleus) prior to harvesting at day 0 (Figure 2(a)). The cell morphology started to change with the application of Cellartis DE differentiation kit. At day 5 the cells showed some morphology indicative of DE, and on day 7 the shape of the cells became more spikey or triangular, which is the typical DE morphology having reached confluence (Figure 2(a)). The cells were dissociated and replated, and hepatocyte differentiation was performed by applying a prototype of Cellartis Hep differentiation kit. The hepatocyte differentiation protocol is schematically described in Figure 1. The typical DE cell morphology changed during the application of HEP progenitor medium (Figure 2(b)) and after the application of HEP maturation medium the cells gradually acquired the hepatocyte morphology (Figure 2(c)). Finally, when the cells were cultured in HEP maintenance medium, they acquired the typical hepatocyte morphology, and polygonal single- or binucleated cells were observed (Figure 2(d)).

3.2. Gene Expression of Lineage-Specific Markers

For each hPSC line, RNA was collected daily throughout the differentiation process and subsequently analyzed using RT-qPCR for the lineage-specific markers listed in Table 2. Figure 3 shows the relative quantification curves for the early stages markers, in addition to pairwise cell line correlation tables for each marker. The pluripotency markers OCT4 and NANOG were distinctly downregulated early during the differentiation process; OCT4 was expressed below the detection limit ( ≥ 35) already at day 4 and NANOG at day 7. The average pairwise correlation coefficients between cell lines for these two markers are > 0.9 (Figure 3), indicating very high synchroneity among the cell lines at this stage. The expression of T (Brachyury), a pan-mesoderm marker expressed in mesendoderm which is a precursor of both mesoderm and endoderm [19], peaks at day 2 in all cell lines (Figure 4). Figure 5 shows the onset of the DE markers SOX17 and CXCR4 at day 3 and the average correlation coefficients for these markers during day 2 to day 10 are very high (0.85 and 0.98, resp.). The expression of SOX17 decreased gradually until it fell below the detection limit at day 10. The expression of CXCR4 was upregulated until day 5 or day 6, and then it was downregulated and subsequently undetectable at day 9. The onset of the DE marker CER1 occurred already at the mesendoderm stage (day 2), one day earlier than SOX17 and CXCR4, and its expression increased until day 6 after which it started to decrease and, similar to CXCR4, it was below the detection limit at day 9. The average correlation coefficient for CER1 is very strong (0.90) and there is no substantial difference in CER1 expression between the cell lines. HHEX, a marker for ventral foregut endoderm, was also expressed at the DE stage and subsequently undetectable at day 11 (except for line AS034), with a very strong average correlation coefficient of 0.86 as shown in Figure 5. In general, the correlation analysis does not show any preference of hESC lines to correlate with each other rather than with hiPSC lines or vice versa (Figures 3, 4, and 5).

The correlation between cell lines regarding markers of stages following the DE phase of the hepatic differentiation is slightly lower compared to the early markers (Figures 6 and 7). Due to transient fluctuations in the RNA levels on the days after each medium change, days 8, 10, 12, 13, 15, 17, 19, 20, 22, 24, 26, 27, 29, 31, 33, and 34 were not included in the correlation analysis. The genes TBX3, HNF4a, HNF6, and AFP were expressed already at the hepatoblast stage. These genes demonstrated gene regulation synchronicity among all cell lines and, as shown in Figure 6, the average pairwise correlation ranges from moderate (0.52 for HNF4a) through strong (0.60 for HNF6 and 0.63 for AFP) to very strong (0.83 for TBX3). The correlation of the mature hepatocyte markers ranges from weak (0.38 for CYP3A4), through moderate (0.41 for PROX1 and 0.57 for AAT), to strong (0.75 for both KRT18 and ALB) (Figure 7). Although the weakest average correlation was shown for CYP3A4, there are some strong and very strong correlations between pairs of cell lines for this gene, for example, 0.89 between ChiPSC6b and P11025 (Figure 7). Interestingly, and as noted above for the DE stage, there is no preference for hESC lines to correlate with each other rather than with hiPSC lines at later stages either, and the same applies to the hiPSC lines. The expression profiles for the different genes show minor fluctuations during the hepatic differentiation; however, the distinct changes in gene expression occurred in general at the same time for the different cell line, further underscoring the synchronized differentiation process across the cell lines.

3.3. Immunocytochemical Analysis of Lineage-Specific Markers during Hepatic Differentiation

The protein expression of selected markers from the different developmental stages was analyzed by immunocytochemistry. Figure 8 shows the homogenous expression of the pluripotent marker Oct4 in hPSCs in addition to the absence of the differentiation marker SSEA-1 (Figures 8(a)8(d)), demonstrating the undifferentiated state of the hPSC at the start of the differentiation protocol. At days 5 and 7, all cells expressed the DE marker Sox17 and the pluripotency marker Oct4 was absent (Figures 8(e)8(h) and 8(i)8(l), resp.), illustrating the high efficiency in generating DE cells using the differentiation kit.

During the differentiation from DE cells to hepatocytes, hepatic markers were gradually upregulated. Figure 9 shows the expression of CK18, AFP, and HNF4a at day 14. The hepatic marker CK18 was weakly expressed (Figure 9(a)), while AFP and HNF4a were strongly expressed in most of the cells (Figures 9(b) and 9(c), resp.).

At day 25, the differentiation has progressed and more mature hepatocyte markers were expressed in the cells. Figure 10(a) shows the expression of CK18, which was remarkably denser at day 25 than at day 14. HNF4a was still expressed at day 24 at a similar level as on day 14 (Figure 10(b)). Coexpression of ALB and AFP at day 25 was detected in some hepatocyte-like cells; however, the cell cultures were heterogeneous since in some cells only AFP was expressed, which indicated a fetal-like phenotype (Figure 10(c)).

At day 29, expression of AFP was still present although it was weaker than at day 25. At this stage, the cells were still heterogeneous with about 50% of the cells expressing only ALB and the remaining 50% coexpressing AFP and ALB (Figure 11(a)) indicating the immaturity of some cells at this point. Coexpression of AAT and AFP was also detected (Figure 11(b)); however, there were still some cells that only expressed AFP. At day 30, mature hepatic markers were expressed, such as CYP3A4 (Figure 12(a)); however, not all cells were immunopositive. In addition, HNF4a was still expressed in all hepatocyte-like cells (Figure 12(b)).

Figure 13 shows an overview of the expression patterns of all the genes analyzed in this study, considering genes as being expressed if < 35. The culturing medium of the different stages during hepatic differentiation as well as the days after start of differentiation is indicated in the upper bars. The pluripotency genes, OCT4 and NANOG, were expressed from day 0 and their expression partly overlapped the DE stage. The gene (Brachyury) was only expressed at day 2 indicating the mesendoderm stage. The genes CER1 and HHEX were initiated already at day 2 and CXCR4 and SOX17 appeared at day 3, indicating the onset of the DE differentiation. Progenitor and hepatocyte markers were expressed gradually after adding HEP progenitor medium. TBX3 and HNF4A were already present at day 8, which is one day after the shift to HEP progenitor medium (2). HNF6 appeared on day 10 and the fetal hepatocyte marker AFP on day 11. The expression of PROX1 and KRT18 was detected at day 15, one day after the shift to HEP maturation medium base (3Ap) with supplement (3Bp). The hepatocyte maturation marker AAT was already expressed at day 18. ALB was present from day 20 and, notably, only a few days after the addition of HEP maintenance medium (4) the adult enzyme CYP3A4 was expressed at day 23.

3.4. Clustering Analysis

In order to detect possible coregulation and similarities between all the genes that were analyzed in this study except transporters SLC10A1 (NTCP), ABCB11 (BSEP), SLCO1B1 (OATP1B1), and ABCC2 (MRP2), clustering analyses of the gene expression were performed both globally and locally for different intervals during the hepatic differentiation. The clustering of genes was performed using each gene’s median expression value over all cell lines, with Spearman’s rank correlation as the similarity function. The clustering of days 0 to 11 shows a clear separation between two clusters, with one containing the pluripotency markers, OCT4 and NANOG, and the primitive streak marker, , and the other cluster containing the DE markers SOX17, CXCR4, CER1,  and HHEX, the ventral foregut marker (Figure 14(a)). In the clustering of genes days 14 to 35 of the hepatic differentiation, the main separation is between a cluster containing the two genes TBX3 and AFP and a second cluster containing the remaining genes. In the later cluster, HNF4A and HNF6 are clearly separated from a subcluster containing PROX1, CYP3A4, ALB, AAT, and KRT18 (Figure 14(b)). Notably, in the analysis of days 7 to 21, HNF6 is clearly separated from all other genes. For the remaining genes, there were one subcluster consisting of HNF4A and AFP and a second subcluster consisting of TBX3, PROX1, and KRT18 (Figure 14(c)). For the maturation phase (days 21 to 35) two main clusters were identified, one containing HNF4A, TBX3, and AFP and the other containing PROX1, AAT, HNF6, KRT18, ALB, and CYP3A4 (Figure 14(d)).

3.5. Gene Expression and Immunocytochemistry Analysis of Drug Transporters

To determine the maturity of the hepatocyte-like cells generated from the different hPSC used in this study, RT-qPCR was applied to analyze the expression of the drug transporters SLC10A1 (NTCP), ABCB11 (BSEP), SLCO1B1 (OATP1B1), and ABCC2 (MRP2). Figure 15 shows interindividual variation in drug transporters gene expression in hepatocyte-like cells derived from the different hPSC lines (Figure 15(a)15(d)). In addition, the expression of NTCP (Figure 15(a)) and MRP2 (Figure 15(b)) was closer to the level of human freshly isolated primary hepatocytes (calibrator) than OATP1B1 (Figure 15(c)) and BSEP (Figure 15(d)). Most of the interindividual variation was observed for BSEP (Figure 15(d)), where hepatocyte-like cells derived from AS034 at day 34 expressed BSEP at higher levels than any of the other hPSC-derived hepatocytes. OATP1B1 also showed high interindividual variation, where hepatocytes derived from SA181 and P11012 at day 3 expressed OATP1B1 at higher levels than what were observed in the other cell lines.

Immunocytochemistry analyses were performed to confirm the expression of NTCP, BSEP, MRP2, and OATP1B1 at the protein level. Figure 16 shows the staining patterns for NTCP and OATP1B1 and Figure 17 shows the expression of BSEP and MRP2.

3.6. Cytochrome P450 (CYP) Enzymes Activity Assay

To investigate the drug metabolizing capacity, hepatocyte-like cells and cryoplateable human primary hepatocytes (hphep) were incubated in a cocktail of phenacetin (metabolized by CYP1A), bufuralol (metabolized by CYP2D6), diclofenac (metabolized by CYP2C9), midazolam (metabolized by CYP3A), and mephenytoin (metabolized by CYP2C19) at day 29 of the hepatic differentiation. The concentrations of the resulting metabolites paracetamol, 1-OH-bufuralol, 4-OH-diclofenac, 3-OH-midazolam, and 4-OH-mephenytoin were determined by liquid chromatography/mass spectrometry. The metabolite concentrations were normalized to mg protein and incubation time. Figure 18 shows interindividual variation in the different CYP enzyme activities in the hepatocyte-like cells generated from the different hPSC lines. The activity of CYP1A in hphep is about 7 times higher than in AS034-derived hepatocytes (Figure 18(a)). However, the activity of CYP3A in SA034-derived hepatocytes was higher than in hphep (Figure 18(b)). The activity of CYP2C9 in hphep is about 4 times higher than in ChiPSC6b-derived hepatocytes (Figure 18(c)). The activity of CYP2D6 in hphep is much higher than in hPSC-derived hepatocytes (Figure 18(d)). Moreover, the activity of CYP2C19 in hphep is about 4 times higher than ChiPSC6b-derived hepatocytes (Figure 18(e)). In addition, hepatocyte-like cells from SA034 show much high CYP1A and CYP3A activity compared to other hPSC-derived hepatocytes (Figures 18(a) and 18(b), resp.). Hepatocyte-like cells derived from ChiPSC6b show higher CYP2C9 activity compared to hepatocytes-like cells derived from the other cell lines (Figure 18(c)). These results illustrate the interindividual variation in CYP activity of hPSC-derived hepatocytes.

3.7. PAS Staining

The ability to produce and store glycogen is a function of mature hepatocytes [11]. To investigate if hPSC-derived hepatocytes also have the ability to store glycogen PAS staining was performed. Figure 19 shows the detection of glycogen storage by PAS. Hepatocytes derived from both hESC (Figure 19(b)) and hiPSC (Figure 19(a)) show glycogen storage ability.

4. Discussion

The unique properties of pluripotent stem cells, including their indefinite self-renewal and their capacity to differentiate to essentially all cell types in the body, make them an attractive source for human cells that can be applied in various cell models for drug discovery and future regenerative medicine applications [2, 4, 5, 7, 15, 20, 21]. In vitro differentiation of hepatocytes, recapitulating some of the properties and functionalities of their in vivo counterpart, has been reported by several groups using differentiation protocols that mimic the hepatocyte development in vivo [4, 69, 15, 22]. A recent study reported a standardized hepatocyte differentiation protocol that does not require any further adjustments to produce near-homogenous hepatocytes from a large panel of different hPSC lines [13]. In the present study, we have differentiated six hPSC lines into hepatocyte-like cells applying a protocol developed further from the procedure published by Asplund and coworkers [13]. Using RT-qPCR, we analyzed the gene expression of several key lineage-specific genes that are markers for the different stages during hepatocyte differentiation to assess the synchronicity of the in vitro differentiation process. In addition, we applied statistical methods to mathematically analyze and quantify the correlation between the hPSC lines. The results revealed highly synchronized gene expression profiles, especially for key markers of the early differentiation stages, thus indicating the similarity of this in vitro differentiation process to the in vivo liver development. However, weak correlation of the mature hepatocyte marker CYP3A4 could be explained by its high level of polymorphism [23]. We also noted that the correlation patterns among hESC and hiPSC lines appeared randomly distributed and no evidence of preferential similarity between specific cell lines was observed.

The hepatic differentiation process starts with the downregulation of the stem cell markers OCT4 and NANOG that are also clustered together indicating similar functionality, such as maintenance of pluripotency, and both genes have been indeed reported to control the expression of each other [24]. NANOG clustered also with T (Brachyury), and NANOG has been reported to bind the promoter region of T [25]. Our results also show that OCT4 is undetectable in DE cells while NANOG is downregulated but still present at low levels at the DE stage, which is also consistent with the results from other studies [26, 27]. The primitive streak stage appears at day 2 with a short peak expression of T, which is then undetectable already on day 3, in parallel with the onset of expression of SOX17 and CXCR4, indicating the termination of the mesendoderm stage and the initiation of the DE stage [19, 27]. SOX17 and CXCR4 also clustered together at the DE stage, which is expected since CXCR4 is regulated by SOX17 [27]. CER1 is typically used as DE marker in combination with other genes, since it is also expressed in mesoderm [28]. Our results indicate that, unlike SOX17 and CXCR4, the onset of CER1 occurs in the primitive streak, which is in agreement with in vivo liver development [29]. HHEX promotes the further hepatic differentiation by terminating the DE stages, thereby initiating hepatoblast differentiation. The onset of HHEX expression is suggested to occur at the DE stage and continue through the hepatoblast stage [30]. Our results demonstrate the upregulation of HHEX in the mesendoderm and its expression is terminated at the hepatoblast stage. HHEX also cluster with CER1, and both of these genes are known to be induced by SOX17. This was, however, not reflected in our results, since CER1 and HHEX were expressed before SOX17. In addition, HHEX is required for the normal expression of CER1, which may explain the clustering of this pair of genes with SOX17 and CXCR4 [28]. However, the expression of HHEX was terminated at the later hepatoblast stage, whereas in vivo expression of HHEX is maintained throughout the hepatic development [14].

Small fluctuations in the RNA levels were observed as an artifact at each medium change after the DE stage and these were not included in the gene expression and clustering analysis since they would mask the real effects when the gene expression is stabilized and introduce nonrelevant noise. The genes TBX3 and HNF4A are known to be expressed in the hepatic endoderm stage [1, 4, 14, 31, 32]. Interestingly, these genes are induced directly after the application of HEP progenitor medium (2) indicating the efficiency of the medium in promoting the development into hepatoblasts. TBX3 is proposed to promote hepatocyte differentiation from hepatoblasts and represses cholangiocytes by downregulating HNF6 and KRT18 and additionally promotes the expression of HNF4A, which is a key regulator of morphological and functional differentiation of hepatocytes [2], by repressing the transcriptional repressor of HNF4A [32]. HNF6 is expressed at the hepatoblast stage and promotes the differentiation of hepatoblasts towards cholangiocytes [14, 32]. However, HNF6 is required for proper liver development in the early stages [33]. Towards the end of the hepatoblast stage, AFP expression is detected, which is a fetal hepatocyte marker expressed until birth. Subsequently, it is downregulated but can still be detected in adult liver at very low levels [34]. Our results show that AFP is coexpressed in some hepatocyte-like cells with the mature hepatocyte markers AAT and ALB and is downregulated in the maturing hepatocyte-like cells, however, not to a level below the detection limit of the assay (Figure 6). PROX1 and KRT18 are upregulated at day 15 (Figure 7), directly after the switch to HEP maturation base medium (3Ap) and supplement (3Bp). PROX1 together with HNF6 was demonstrated to be crucial for complete hepatocyte programming including recapitulating the metabolic functionality in vitro [31]. KRT18 is a hepatic marker which we observed to be weakly expressed in hepatoblasts and which was upregulated in later stages (Figure 7), which is in accordance with other studies [35]. AAT is detected at day 19 at low levels compared to freshly isolated primary hepatocytes. ALB, which is a mature hepatocyte marker, is detected at day 20. This gene could also be expressed in nonfunctional hepatocytes when the programming process fails to mimic liver organogenesis [31]. However, the detection of CYP3A4 mRNA expression (Figure 7) and CYP3A4 immunopositive hepatocyte-like cells (Figure 12) as well as CYP activity assay results that show comparable results to cryoplateable human primary hepatocytes (Figure 18) confirmed the hepatic functionality of the generated hepatocyte-like cells. In addition, the RNA and protein expression of the drug transporters MRP2, OATP1B1, BSEP, and NTCP (Figures 16 and 17), as well as the ability to store glycogen (Figure 19), also demonstrate the hepatic functionality of these cells. The interindividual variation in CYP activity and drug transporters expression in hPSC-derived hepatocytes show similarity to what is typically observed in their in vivo counterparts [11, 13]. However, unlike during the in vivo liver development [14], ALB is not detected in hepatoblasts in our study.

The clustering analysis of the later differentiation stages reveals the shift of the cluster PROX1, TBX3, KRT18, HNF4A, and AFP at days 7 to 21 to the cluster HNF4A, AFP, and TBX3, and the cluster PROX1, AAT, HNF6, ALB, CYP3A4, and KRT18 at days 21 to 35. The clustering of PROX1 and KRT18 both between days 7 and 21 and between days 21 and 35 could be explained by the upregulation of both genes when switching to the HEP maturation base medium (3Ap) and supplement (3Bp). Importantly, PROX1 and HNF6 were described to be involved in the same gene regulatory network controlling the migration and adhesion of hepatocytes in vivo [33, 36]. Since HNF6 and KRT18 are both regulated by TBX3 [32] it is plausible that PROX1 and KRT18 are involved in the same gene regulatory network. HNF4a is known to bind to more than 40% of liver active genes [2], and its expression is already upregulated at day 8, which could explain its clustering with AFP and TBX3, which are also upregulated early (Figure 13). At days 21 to 35 there is a clear distribution of mature hepatocyte markers (AAT, ALB, KRT18, and CYP3A4) into adjacent clusters separated from earlier markers (AFP, TBX3). Finally, the clustering of HNF6 with KRT18 could possibly be explained by the common regulation by TBX3 [32]; however, the clustering of ALB with HNF6 needs to be further investigated.

5. Conclusion

The process of differentiating hPSCs into hepatocytes used in the present study demonstrated highly synchronized gene expression profiles of several lineage-specific genes across 6 hPSC lines. Comparing these data to the results from previous studies of both in vitro and in vivo differentiated hepatocytes revealed important similarities but also some differences, such as the absence of coexpression of PROX1 and HNF6, which promotes the induction of HNF1A. Furthermore, the silencing of HHEX at early stages also deviates from the in vivo situation. A successful correction of these deviations would have the potential to significantly improve the functionality of in vitro derived hepatocytes. Moreover, further investigation of the interaction between ALB and HNF6 could also lead to improvements of future differentiation protocols. Taken together, this study adds yet another piece of information to the efforts of improving in vitro hepatic differentiation protocols, thereby bringing hPSC-derived hepatocyte based models to a wider practical use.

Conflict of Interests

The authors Josefina Edsbagge and Barbara Küppers-Munther are employees of Takara Bio Europe AB. The author Mariska Van Giezen was employed by Takara Bio Europe AB during the course of this work.

Acknowledgments

This work was supported by Takara Bio Europe AB (Gothenburg, Sweden) and the University of Skövde, Sweden, under grants from the Knowledge Foundation [2012/0310] and [2013/89].

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