Dedifferentiation of Primary Hepatocytes is Accompanied with Reorganization of Lipid Metabolism Indicated by Altered Molecular Lipid and miRNA Profiles

International Journal of Molecular Sciences Article Dedifferentiation of Primary Hepatocytes is Accompanied with Reorganization of Lipid Metabolism Indicated by Altered Molecular Lipid and miRNA Profiles Mostafa Kiamehr 1,* , Laura Heiskanen 2, Thomas Laufer 3,4 , Aneta Düsterloh 3, Mustafa Kahraman 3,5, Reijo Käkelä 6, Reijo Laaksonen 1,2 and Katriina Aalto-Setälä 1,7 1BioMediTech, Faculty of Medicine and Health Technology, Tampere University, 33520 Tampere, Finland; [email protected] (R.L.); [email protected] (K.A.-S.) 2Zora Biosciences, 02150 Espoo, Finland; [email protected] 3Hummingbird Diagnostics GmbH, 69120 Heidelberg, Germany; [email protected] (T.L.); [email protected] (A.D.); [email protected] (M.K.) 4Department of Human Genetics, Saarland University, 66421 Homburg, Germany 5Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany 6Helsinki University Lipidomics Unit, Helsinki Institute for Life Science (HiLIFE) and Molecular and Integrative Biosciences Research Programme, University of Helsinki, FI-00014 Helsinki, Finland; [email protected] 7Heart Hospital, Tampere University Hospital, 33520 Tampere, Finland *Correspondence: [email protected] Received: 21 May 2019; Accepted: 11 June 2019; Published: 14 June 2019   Abstract: Aim: Primary human hepatocytes (PHHs) undergo dedifferentiation upon the two-dimensional (2D) culture, which particularly hinders their utility in long-term in vitro studies. Lipids, as a major class of biomolecules, play crucial roles in cellular energy storage, structure, and signaling. Here, for the first time, we mapped the alterations in the lipid profile of the dedifferentiating PHHs and studied the possible role of lipids in the loss of the phenotype of PHHs. Simultaneously, differentially expressed miRNAs associated with changes in the lipids and fatty acids (FAs) of the dedifferentiating PHHs were investigated. Methods: PHHs were cultured in monolayer and their phenotype was monitored morphologically, genetically, and biochemically for five days. The lipid and miRNA profile of the PHHs were analyzed by mass spectrometry and Agilent microarray, respectively. In addition, 24 key genes involved in the metabolism of lipids and FAs were investigated by qPCR. Results: The typical morphology of PHHs was lost from day 3 onward. Additionally, ALB and CYP genes were downregulated in the cultured PHHs. Lipidomics revealed a clear increase in the saturated fatty acids (SFA) and monounsaturated fatty acids (MUFA) containing lipids, but a decrease in the polyunsaturated fatty acids (PUFA) containing lipids during the dedifferentiation of PHHs. In line with this, FASN,SCD,ELOVL1,ELOVL3, and ELOVL7 were upregulated but ELOVL2 was downregulated in the dedifferentiated PHHs. Furthermore, differentially expressed miRNAs were identified, and the constantly upregulated miR-27a and miR-21, and downregulated miR-30 may have regulated the synthesis, accumulation and secretion of PHH lipids during the dedifferentiation. Conclusion: Our results showed major alterations in the molecular lipid species profiles, lipid-metabolizing enzyme expression as wells as miRNA profiles of the PHHs during their prolonged culture, which in concert could play important roles in the PHHs’ loss of phenotype. These findings promote the understanding from the dedifferentiation process and could help in developing optimal culture conditions, which better meet the needs of the PHHs and support their original phenotype. Int. J. Mol. Sci. 2019,20, 2910; doi:10.3390/ijms20122910 www.mdpi.com/journal/ijms Int. J. Mol. Sci. 2019,20, 2910 2 of 20 Keywords: primary human hepatocytes (PHHs); dedifferentiation; lipidomics; mass spectrometry; sphingolipids (SLs); phospholipids (PLs); saturated fatty acids (SFAs); monounsaturated fatty acids (MUFAs); polyunsaturated fatty acids (PUFAs); microRNAs (miRNAs) 1. Introduction Primary human hepatocytes (PHHs) are commonly used as the “gold standard” model system to study liver physiology and disease, drug-induced liver injury, active drug transport mechanisms, and drug-drug interactions [ 1 – 3 ]. In addition, hepatocytes handle many crucial metabolic functions of the liver including the synthesis of fatty acids (FAs), cholesterol, cholesteryl esters, triacylglycerols (TAGs), and phospholipids (PLs), and utilizing these lipids together with apolipoproteins produce lipoprotein particles [ 4 ]. PHHs are sensitive to hepatitis C virus infection [ 5 ] and are able to express cytochrome P450 enzymes and drug transporters at significantly higher levels than most hepatoma cell lines such as HepG2 and Huh7 [ 6 ]. Since the availability of the PHHs is limited, scientists have tried to utilize other sources such as rodent primary hepatocytes or stem cell-derived hepatic cells as in vitro cell models. However, none of the so far developed hepatic models are yet as functional and relevant as PHHs in mimicking the complex physiology of the liver. Upon liver injury, hepatic cells are able to rapidly proliferate and regenerate even a large area of the damaged organ [ 7 ]. Despite this extraordinary and unique feature, when hepatocytes are isolated and cultured in vitro , they are unable to expand and progressively lose their unique liver-specific functions [ 8 , 9 ], which typically limits their usability to a few days. This feature is known as “dedifferentiation” and significantly hampers the application of the PHHs particularly in long-term toxicity and xenobiotic biotransformation studies. It is known that the PHHs’ loss of phenotype is primarily a consequence of fundamental gene expression changes and diminished liver-enriched transcription factors triggered by the stress during isolation, disruption of the normal tissue architecture [ 8 , 10 ]. On the other hand, the current culture systems are not able to restore these phenotypical changes due to the lack of critical survival factors essential for liver-specific gene expression [ 8 ]. 3D culture of PHHs alone or together with microfluidic systems and in coculture with other cell types such as mesenchymal stem cells have been shown to improve the PHHs’ life span and functionality [ 11 – 15 ]. However, the conventional 2D culture of PHHs is still the most common approach due to its simplicity and low cost particularly for high-throughput studies. Although, in this culture system, PHHs undergo progressive deterioration of their in vivo -like morphological and functional phenotype [16]. The “-omics” approaches have been broadly utilized to map the changes in the transcriptome and proteome of the dedifferentiating hepatocytes [ 17 – 21 ]. It has been shown that proteins responsible for cytoskeletal remodelling as well as carbohydrate, amino acid and lipid metabolism networks are differentially expressed in dedifferentiating hepatocytes [ 21 ]. In addition, a recent study showed that energy production is decreased during the dedifferentiation through changes in the expression of mitochondrial-associated proteins, particularly those involved in FA and lipid metabolism [ 18 ]. Furthermore, a transcriptomic study on noncoding RNAs showed that FA metabolism is among the most affected pathways during dedifferentiation [ 22 ]. Despite the apparent importance of the lipids in the process of dedifferentiation, surprisingly, no study has been conducted yet on mapping the alterations in the lipid molecular species of the dedifferentiating hepatocytes. This has been partially due to the technical challenges, but the field of lipidomics is now well advanced and the approach using mass spectrometry can be utilized to better understand the role of molecular lipids in various physiological states including dedifferentiation. Such detailed analysis is required since mammalian cells produce thousands of lipids with various organelle-specific structural and functional roles. In addition, cells synthesize hundreds of proteins to control the lipid metabolism and their trafficking and secretion [ 23 ]. Therefore, an in-depth portrait of the temporal changes in the lipid profile Int. J. Mol. Sci. 2019,20, 2910 3 of 20 and the associated genes and microRNAs (miRNAs) of the dedifferentiating hepatocytes is required to understand the complex protein-lipid interplay during the dedifferentiation process. With this new knowledge, we can optimize culture conditions and thereby improve both the phenotype and life span of the cultured PHHs. Here, for the first time, we studied the alterations in the lipidome of the dedifferentiating primary human hepatocytes. To allow unrestricted dedifferentiation, PHHs were cultured in confluent 2D monolayer and their morphology, liver-specific gene expression, and function were monitored during the five days in culture. Most importantly, the lipidome changes in PHHs together with the alterations in the enzymes metabolizing FAs and lipids were studied during the dedifferentiation process. As miRNAs have been shown to be one important driver of hepatic dedifferentiation [ 22 ], alongside lipidomic studies, the temporal changes in the miRNA profile of the dedifferentiating PHHs were also investigated. 2. Results 2.1. The Morphology, Gene Expression, and Functionality of PHHs PHHs remained viable and confluent throughout the five days in the culture. However, they started to lose their characteristic hepatocyte morphology from day 3 onward and at day 5, cells had completely lost their typical polygonal structure and exhibited a flattened appearance with weakly defined cell-to-cell borders (Figure 1A) which implied that the PHHs were dedifferentiating. Using qPCR, the expression of three liver-specific genes was assessed in the dedifferentiating PHHs (Figure 1B). FOXA2 expression was downregulated by 5-fold at day 1 compared to day 0 and its expression remained low until day 5. Similar to FOXA2, the expression of ALB was dramatically downregulated by 58-fold at day 1 compared to day 0 and remained low afterwards. The expression of AFP fluctuated in the cultured PHHs and, depending on the time point, its level was 10to 40-fold higher than that in our control sample, hLTR. In order to assess the functionality of the PHHs at the gene level, the expression of four of the CYP isoforms known to be important in drug metabolism, lipid homeostasis, and cholesterol biosynthesis [24–26] was evaluated in the dedifferentiating PHHs (Figure 1B). CYP1A2 was downregulated by about 120-fold after the PHHs were cultured for one day. Similarly, CYP7A1 and CYP51A1 were both downregulated by approximately 2and 3-fold during the first day of culture. The expression of CYP3A4, was downregulated already before the culture since it’s expression levels at day 0 was 18-fold lower than that in the reference hLTR sample. Interestingly, the expression of all four CYP genes was slightly recovered either at day 2 or day 5 of the cell culture. The functionality of the PHHs was assessed also biochemically by measuring the secreted TAG, albumin, and urea in the medium of the cultured PHHs at day 2 and 5. No changes were observed in the ability of the PHHs to secrete TAG and urea between day 2 and day 5 (Figure 1C). Interestingly however, the amount of albumin secreted by PHHs at day 5 had increased by 55% compared to its amount at day 2, which correlated well with our observation from the expression of ALB at the gene level. Int. J. Mol. Sci. 2019,20, 2910 4 of 20 Int. J. Mol. Sci. 2019, 20, x FOR PEER REVIEW 4 of 22 Figure 1. Evaluation of the morphology and functionality of primary human hepatocytes (PHHs) during the course of dedifferentiation. (A) Phase contrast images showing the morphology of the PHHs at days 1, 2, and 5 of the culture. The scale bar represents 200 µm. (B) qPCR analysis of FOXA2, ALB, AFP, CYP1A2, CYP3A4, CYP7A1 and CYP51A1 genes at days 0, 1, 2, and 5. The gene expression data for FOXA2, ALB, and AFP was normalized to housekeeping gene, GAPDH, and CYP genes were normalized to both GAPDH and B2M. The values are presented relative to the human liver total RNA (hLTR) sample. Each sample was run in technical triplicate and bars represent mean ± SD of three biological replicates. (C) Biochemical analysis of the conditioned media of the PHHs for secreted triacylglycerol (TAG), albumin, and urea at day 2 and 5 of the culture. Values are presented per well, per 24 h. Bars represent mean ± SD of at least three biological replicates. Using qPCR, the expression of three liver-specific genes was assessed in the dedifferentiating PHHs (Figure 1B). FOXA2 expression was downregulated by 5-fold at day 1 compared to day 0 and its expression remained low until day 5. Similar to FOXA2, the expression of ALB was dramatically Figure 1. Evaluation of the morphology and functionality of primary human hepatocytes (PHHs) during the course of dedifferentiation. ( A ) Phase contrast images showing the morphology of the PHHs at days 1, 2, and 5 of the culture. The scale bar represents 200 µ m. ( B ) qPCR analysis of FOXA2, ALB,AFP,CYP1A2,CYP3A4,CYP7A1 and CYP51A1 genes at days 0, 1, 2, and 5. The gene expression data for FOXA2,ALB, and AFP was normalized to housekeeping gene, GAPDH, and CYP genes were normalized to both GAPDH and B2M. The values are presented relative to the human liver total RNA (hLTR) sample. Each sample was run in technical triplicate and bars represent mean ± SD of three biological replicates. ( C ) Biochemical analysis of the conditioned media of the PHHs for secreted triacylglycerol (TAG), albumin, and urea at day 2 and 5 of the culture. Values are presented per well, per 24 h. Bars represent mean ±SD of at least three biological replicates. 2.2. Alterations in the Lipid Profile of the PHHs The lipid profile in the dedifferentiating PHHs was studied by mass spectrometry and a total of 139 molecular species spanning 19 cholesteryl esters (CEs), 16 ceramides, 10 diacylglycerols (DAGs), Int. J. Mol. Sci. 2019,20, 2910 5 of 20 7 globotriaosylceramides (Gb3s), 9 glucosyl/galactosylceramides (Glc/GalCers), 7 lactosylceramides (LacCers), 2 lyso-phosphatidylcholines (LPCs), 7 lyso-phosphatidylethanolamines (LPEs), 1 lyso-phosphatidyl glycerol (LPG), 3 lyso-phosphatidylinositols (LPIs), 1 lyso-phosphatidylserine (LPS), 30 phosphatidylcholines (PCs), 7 phosphatidylethanolamines (PEs), 3 phosphatidylinositols (PIs), and 17 sphingomyelins (SMs) were detected in the cultured PHHs at days 0, 1, 2, and 5 (Table S2). Our data showed that the levels of sphingolipids (SLs) increase, but the levels of phospholipids (PLs) decrease in the dedifferentiating PHHs (Figure 2A). In fact, the total concentration of ceramide, LacCer, Glc/GalCer, and Gb3 increased in PHHs by 4.8-, 5.3-, 10.3-, and 4-fold, respectively from day 0 to day 5. On the other hand, the total concentration of PE and PI decreased by about 1.5and 2-fold respectively, from day 0 to day 5. The total PC remained relatively constant during the culture of the PHHs. The total CE content was reduced in PHHs-d1 by almost 10-fold compared to PHHs-d0 and its concentration remained low during the rest of the culture. The total amount of the DAG fluctuated in PHHs. Int. J. Mol. Sci. 2019, 20, x FOR PEER REVIEW 6 of 22 Figure 2. Alterations in the lipid profile of the PHHs during the dedifferentiation. Lines describe the detected concentration (pmol/µg total protein) of (A) different lipid classes, (B) molecular sphingolipid (SL) species, and (C,D) molecular phospholipid (PL) and diacylglycerol (DAG) species detected in PHHs at days 0, 1, 2, and 5; ’d’ represents days in culture. Panel C shows the PL molecular species that decreased, and panel D the species that increased during the dedifferentiation. Bars in A represent mean ± SD of three biological replicates. The detailed values of lipidomics is provided in the Table S2. CE = cholesteryl ester, Cer = ceramide, DAG = diacylglycerol, Gb3 = globotriaosylceramide, Glc/GalCer = glucosyl/galactosylceramide, LacCer = lactosylceramide, PC = phosphatidylcholine, PE = phosphatidylethanolamine, PI = phosphatidylinositol, SM = sphingomyelin. Monitoring the individual molecular species in PHHs during the culture period demonstrated that the concentration of almost all molecular SL species was increasing over time, particularly between day 2 and day 5 (Figure 2B). The only exceptions were Glc/GalCer d18:1/23:0, SM d18:0/23:0, SM d18:1/23:0, SM d18:1/23:1, and SM d18:1/26:2. Interestingly, the increase was more pronounced in SLs containing long-chain FAs (LCFAs, C16-22) compared to those SLs containing very-long-chain FAs (VLCFAs, C22-26). The concentration of PL molecular species also showed temporal changes, and based on the alterations in their concentrations between day 2 and day 5, the PLs could be divided into two groups (Figure 2C,D). In the first group, the species were mainly composed of polyunsaturated FAs (PUFAs, specially 18:2) or highly unsaturated FAs (HUFAs, with 4–6 double bonds) coupled with a saturated FA (SFA). The concentrations in this group were mainly decreasing from day 2 to day 5 (Figure 2C). The second group largely consisted of SFAs and/or monounsaturated FAs (MUFAs), and the PUFA chains found in this group of lipids were restricted to the 20:3 and 20:4 chains. The concentrations in this group, in contrast to the first group, were mainly increasing between day 2 and day 5 (Figure 2D). 2.3. Alterations in the Lipid Metabolism-Related Genes Figure 2. Alterations in the lipid profile of the PHHs during the dedifferentiation. Lines describe the detected concentration (pmol/ µ g total protein) of ( A ) different lipid classes, ( B ) molecular sphingolipid (SL) species, and ( C , D ) molecular phospholipid (PL) and diacylglycerol (DAG) species detected in PHHs at days 0, 1, 2, and 5; ’d’ represents days in culture. Panel C shows the PL molecular species that decreased, and panel D the species that increased during the dedifferentiation. Bars in A represent mean ± SD of three biological replicates. The detailed values of lipidomics is provided in the Table S2. CE =cholesteryl ester, Cer =ceramide, DAG =diacylglycerol, Gb3 =globotriaosylceramide, Glc/GalCer =glucosyl/galactosylceramide, LacCer =lactosylceramide, PC =phosphatidylcholine, PE =phosphatidylethanolamine, PI =phosphatidylinositol, SM =sphingomyelin. Monitoring the individual molecular species in PHHs during the culture period demonstrated that the concentration of almost all molecular SL species was increasing over time, particularly between day 2 and day 5 (Figure 2B). The only exceptions were Glc/GalCer d18:1/23:0, SM d18:0/23:0, SM d18:1/23:0, SM d18:1/23:1, and SM d18:1/26:2. Interestingly, the increase was more pronounced in SLs containing long-chain FAs (LCFAs, C16-22) compared to those SLs containing very-long-chain FAs (VLCFAs, C22-26). Int. J. Mol. Sci. 2019,20, 2910 6 of 20 The concentration of PL molecular species also showed temporal changes, and based on the alterations in their concentrations between day 2 and day 5, the PLs could be divided into two groups (Figure 2C,D). In the first group, the species were mainly composed of polyunsaturated FAs (PUFAs, specially 18:2) or highly unsaturated FAs (HUFAs, with 4–6 double bonds) coupled with a saturated FA (SFA). The concentrations in this group were mainly decreasing from day 2 to day 5 (Figure 2C). The second group largely consisted of SFAs and/or monounsaturated FAs (MUFAs), and the PUFA chains found in this group of lipids were restricted to the 20:3 and 20:4 chains. The concentrations in this group, in contrast to the first group, were mainly increasing between day 2 and day 5 (Figure 2D). 2.3. Alterations in the Lipid Metabolism-Related Genes Several genes related to the synthesis of SLs were evaluated by qPCR in the dedifferentiating PHHs (Figure 3). Ceramide synthesis is orchestrated by a family of six CerSs encoded by CERS1-CERS6 (Figure 4A). CERS1 and CERS5 were upregulated by 1.5and 3-fold, respectively, in PHHs-d1 compared to PHHs-d0. CERS1, however, was gradually downregulated while CERS5 remained upregulated until the end of the culture. In contrast to CERS1 and CERS5,CERS4 was downregulated by 3-fold in PHHs-d1 and remained relatively constant afterwards. The expression of CERS6 was upregulated by 2-fold in PHHs-d2 compared to PHHs-d0. CERS2 was expressed relatively constant throughout the entire culture. Int. J. Mol. Sci. 2019, 20, x FOR PEER REVIEW 7 of 22 Several genes related to the synthesis of SLs were evaluated by qPCR in the dedifferentiating PHHs (Figure 3). Ceramide synthesis is orchestrated by a family of six CerSs encoded by CERS1CERS6 (Figure 4A). CERS1 and CERS5 were upregulated by 1.5and 3-fold, respectively, in PHHsd1 compared to PHHs-d0. CERS1, however, was gradually downregulated while CERS5 remained upregulated until the end of the culture. In contrast to CERS1 and CERS5, CERS4 was downregulated by 3-fold in PHHs-d1 and remained relatively constant afterwards. The expression of CERS6 was upregulated by 2-fold in PHHs-d2 compared to PHHs-d0. CERS2 was expressed relatively constant throughout the entire culture. Figure 3. qPCR analysis of key genes involved in the metabolism of sphingolipids (SLs) studied in PHHs during their five days in the culture. The expression of CERS1, CERS2, CERS4, CERS5, CERS6, ASAH1, ASAH2, SGMS1, SGMS2, SMPD1, and UGCG genes in PHHs at time points day 0, 1, 2, and 5. The expression of each gene was normalized to both GAPDH and B2M as endogenous controls. The values are presented relative to the hLTR sample. Each sample was run in technical triplicate and bars represent mean ± SD of three biological replicates. Figure 3. qPCR analysis of key genes involved in the metabolism of sphingolipids (SLs) studied in PHHs during their five days in the culture. The expression of CERS1,CERS2,CERS4,CERS5, CERS6,ASAH1,ASAH2,SGMS1,SGMS2,SMPD1, and UGCG genes in PHHs at time points day 0, 1, 2, and 5. The expression of each gene was normalized to both GAPDH and B2M as endogenous controls. The values are presented relative to the hLTR sample. Each sample was run in technical triplicate and bars represent mean ±SD of three biological replicates. Int. J. Mol. Sci. 2019,20, 2910 7 of 20 Int. J. Mol. Sci. 2019, 20, x FOR PEER REVIEW 8 of 22 Figure 4. (A) Demonstrates a simplified pathway of sphingolipids (SLs) together with the responsible key genes involved in regulating the pathway. (B) Demonstrates a simplified pathways of de-novo synthesis of fatty acids (FAs) as well as imported essential polyunsaturated FAs (PUFAs) together with responsible genes involved in regulating the pathway (the figure was adapted from Kiamehr et al. [27]). Ceramides are degraded to sphingosine and free FAs by ceramidases encoded by distinct genes like ASAH1 and ASAH2 (Figure 4A). The expression of ASAH1 remained constant throughout the culture, while ASAH2 was downregulated in PHHs by 9-fold after one day in the culture. The expression of ASAH2 remained low until day 5. On the other hand, the expression of SGMS1 and SGMS2 involved in the production of SM from ceramides were constantly upregulating and in PHHsd5, both SGMS1 and SGMS2 were expressed approximately 3-fold higher compared to their levels in PHHs-d0. SM is hydrolyzed by isoforms of sphingomyelinase (SMase) which produce phosphorylcholine and the intracellular effector ceramide. SMPD1 gene encodes a lysosomal acid sphingomyelinase and its expression remained constant during the cell culture of the PHHs. The UDP-glucose:ceramide glucosyltransferase (UGCG) gene encodes the enzyme which catalyzes the first glycosylation step in glycosphingolipid (GSL) biosynthesis. In the cultured PHHs, UGCG was upregulated by 6-fold at day 1 compared to day 0 and remained upregulated during the rest of the culture. 2.4. Alterations in FA Metabolism-Related Genes FA desaturase (FADS) inserts double bonds to pre-existing PUFA precursors (Figure 4B). In our study, FADS1 remained unchanged and FADS2 were upregulated by almost 3-folds at day 5. The genes related to the elongation of verylong-chain fatty acids (ELOVL) work in sequence with the desaturases and are essential for the metabolism of saturated or unsaturated LCFAs and VLCFAs (Figure 4B). ELOVL1, ELOVL3, and ELOVL7 are involved in the elongation of saturated FAs while ELOVL2 and ELOVL5 are mainly involved in elongation of unsaturated FAs. We observed that ELOVL1 was upregulated in PHHs-d1 by 4-fold compared to the expression level in PHHs-d0, and Figure 4. ( A ) Demonstrates a simplified pathway of sphingolipids (SLs) together with the responsible key genes involved in regulating the pathway. ( B ) Demonstrates a simplified pathways of de-novo synthesis of fatty acids (FAs) as well as imported essential polyunsaturated FAs (PUFAs) together with responsible genes involved in regulating the pathway (the figure was adapted from Kiamehr et al. [ 27 ]). Ceramides are degraded to sphingosine and free FAs by ceramidases encoded by distinct genes like ASAH1 and ASAH2 (Figure 4A). The expression of ASAH1 remained constant throughout the culture, while ASAH2 was downregulated in PHHs by 9-fold after one day in the culture. The expression of ASAH2 remained low until day 5. On the other hand, the expression of SGMS1 and SGMS2 involved in the production of SM from ceramides were constantly upregulating and in PHHs-d5, both SGMS1 and SGMS2 were expressed approximately 3-fold higher compared to their levels in PHHs-d0. SM is hydrolyzed by isoforms of sphingomyelinase (SMase) which produce phosphorylcholine and the intracellular effector ceramide. SMPD1 gene encodes a lysosomal acid sphingomyelinase and its expression remained constant during the cell culture of the PHHs. The UDP-glucose:ceramide glucosyltransferase (UGCG) gene encodes the enzyme which catalyzes the first glycosylation step in glycosphingolipid (GSL) biosynthesis. In the cultured PHHs, UGCG was upregulated by 6-fold at day 1 compared to day 0 and remained upregulated during the rest of the culture. 2.4. Alterations in FA Metabolism-Related Genes FA desaturase (FADS) inserts double bonds to pre-existing PUFA precursors (Figure 4B). In our study, FADS1 remained unchanged and FADS2 were upregulated by almost 3-folds at day 5. The genes related to the elongation of verylong-chain fatty acids (ELOVL) work in sequence with the desaturases and are essential for the metabolism of saturated or unsaturated LCFAs and VLCFAs (Figure 4B). ELOVL1,ELOVL3, and ELOVL7 are involved in the elongation of saturated FAs while ELOVL2 and ELOVL5 are mainly involved in elongation of unsaturated FAs. We observed that ELOVL1 was upregulated in PHHs-d1 by 4-fold compared to the expression level in PHHs-d0, and its expression remained upregulated until day 5. ELOVL3 was constantly upregulated from day 0 to day 5. ELOVL7 was expressed at low levels on days 0–2 but was upregulated by 2-fold at day 5 when compared to the level found on day 2. On the other hand, ELOVL2, was downregulated in PHHs-d1 by 3-fold compared to PHHs-d0 and remained low afterwards. Genes active in the beginning of the process of Int. J. Mol. Sci. 2019,20, 2910 8 of 20 de novo synthesis of FAs such as FA synthase (FASN), Stearoyl-CoA desaturase (SCD), and ELOVL6 showed the same pattern of expression and were downregulated in the beginning of the culture but were upregulated and recovered to their original expression towards the end of the culture (Figure 5A). Int. J. Mol. Sci. 2019, 20, x FOR PEER REVIEW 9 of 22 its expression remained upregulated until day 5. ELOVL3 was constantly upregulated from day 0 to day 5. ELOVL7 was expressed at low levels on days 0–2 but was upregulated by 2-fold at day 5 when compared to the level found on day 2. On the other hand, ELOVL2, was downregulated in PHHs-d1 by 3-fold compared to PHHs-d0 and remained low afterwards. Genes active in the beginning of the process of de novo synthesis of FAs such as FA synthase (FASN), Stearoyl-CoA desaturase (SCD), and ELOVL6 showed the same pattern of expression and were downregulated in the beginning of the culture but were upregulated and recovered to their original expression towards the end of the culture (Figure 5A). Figure 5. Real-time qPCR analysis of genes involved in the metabolism of fatty acids (FAs). (A) and glucose homeostasis (B) studied in dedifferentiating PHHs. The expression of (A) FASN, SCD, FADS1, Figure 5. Real-time qPCR analysis of genes involved in the metabolism of fatty acids (FAs). ( A ) and glucose homeostasis ( B ) studied in dedifferentiating PHHs. The expression of ( A )FASN,SCD,FADS1, FADS2,ELOVL1,ELOVL2,ELOVL3,ELOVL5,ELOVL6, and ELOVL7 and ( B )GCK,PKLR, and PCK1 at time points day 0, 1, 2, and 5. The expression of each gene was normalized to both GAPDH and B2M as endogenous controls. The values are presented relative to the hLTR sample. Each sample was run in technical triplicate and bars represent mean ±SD of three biological replicates. 2.5. Alterations in the Genes Related to Glucose Homeostasis Since the lipid metabolism in hepatocytes is highly affected by glucose homeostasis (Figure 4B), we studied the three key genes involved in glycolysis (GCK (encoding glucokiase) and PKLR (encoding liver-type pyruvate kinase)) and gluconeogenesis (PCK1 (encoding phosphoenolpyruvate carboxykinase, thus also known as PEPCK)) of the liver (Figure 5B). All three genes, GCK,PKLR, and PCK1, were downregulated in PHHs after one day in the culture. The expression of both GCK Int. J. Mol. Sci. 2019,20, 2910 9 of 20 and PCK1 was further downregulated in PHHs-d2 and PHHs-d5. PKLR however, was upregulated in PHHs-d2 and recovered its original level of expression at day 5 of the culture. 2.6. Alterations in the miRNA Profile of the PHHs In total, 382 miRNAs were detected in the cultured PHHs at time points day 0, 1, 2, and 5 (Table S3). A heatmap was prepared from all 382 miRNAs detected and according to their expression pattern, miRNAs could be divided into five distinct clusters (Figure 6A,B). Our analysis showed that 23 miRNAs were upregulated and 22 miRNAs were downregulated in PHHs-d5 compared to those in PHHs-d0. The miR-34a, miR-27a, and miR-1246 were the most upregulated and miR-575, miR-4741, and miR-8069 were the most downregulated miRNAs in PHHs-d5. A separate heatmap was prepared from the 30 most differentially expressed miRNAs (Figure 6C). Several differentially expressed miRNAs (shown in red of Figure 6C) have been already associated with functionality or regulating the lipid metabolism of the cells (see Discussion Section). Int. J. Mol. Sci. 2019, 20, x FOR PEER REVIEW 10 of 22 FADS2, ELOVL1, ELOVL2, ELOVL3, ELOVL5, ELOVL6, and ELOVL7 and (B) GCK, PKLR, and PCK1 at time points day 0, 1, 2, and 5. The expression of each gene was normalized to both GAPDH and B2M as endogenous controls. The values are presented relative to the hLTR sample. Each sample was run in technical triplicate and bars represent mean ± SD of three biological replicates. 2.5. Alterations in the Genes Related to Glucose Homeostasis Since the lipid metabolism in hepatocytes is highly affected by glucose homeostasis (Figure 4B), we studied the three key genes involved in glycolysis (GCK (encoding glucokiase) and PKLR (encoding liver-type pyruvate kinase)) and gluconeogenesis (PCK1 (encoding phosphoenolpyruvate carboxykinase, thus also known as PEPCK)) of the liver (Figure 5B). All three genes, GCK, PKLR, and PCK1, were downregulated in PHHs after one day in the culture. The expression of both GCK and PCK1 was further downregulated in PHHs-d2 and PHHs-d5. PKLR however, was upregulated in PHHs-d2 and recovered its original level of expression at day 5 of the culture. 2.6. Alterations in the miRNA Profile of the PHHs In total, 382 miRNAs were detected in the cultured PHHs at time points day 0, 1, 2, and 5 (Table S3). A heatmap was prepared from all 382 miRNAs detected and according to their expression pattern, miRNAs could be divided into five distinct clusters (Figure 6A,B). Our analysis showed that 23 miRNAs were upregulated and 22 miRNAs were downregulated in PHHs-d5 compared to those in PHHs-d0. The miR-34a, miR-27a, and miR-1246 were the most upregulated and miR-575, miR4741, and miR-8069 were the most downregulated miRNAs in PHHs-d5. A separate heatmap was prepared from the 30 most differentially expressed miRNAs (Figure 6C). Several differentially expressed miRNAs (shown in red of Figure 6C) have been already associated with functionality or regulating the lipid metabolism of the cells (see Discussion Section). Figure 6. Influence of prolonged culture of PHHs on their miRNAs expression detected by microarrays. (A) Unsupervised hierarchical clustering of miRNAs using Eucledian distance and Figure 6. Influence of prolonged culture of PHHs on their miRNAs expression detected by microarrays. ( A ) Unsupervised hierarchical clustering of miRNAs using Eucledian distance and complete linkage in the samples. Columns indicate the days of the culture. The expressions of the miRNAs are row-scaled (by time point) and colour coded with blue indicating decreased and red indicating increased expression. miRNAs are clustered in five distinct groups according to their expression pattern marked with coloured boxes and numbers on the left side of the heatmap. The detailed list of miRNAs belonging to each cluster is provided in the Table S3. ( B ) To better illustrate the alterations of miRNAs presented in panel A, box-plots are prepared for each individual cluster at time points day 0, day1, day 2, and day 5. Each box-plot represents the average row-scaled expression of all miRNAs in that specific time point and the bars represent the mean ± SD of the collective miRNAs. Colours on the bottom of each plot is matching the colour of the clusters in the panel A. The numbers of miRNAs included in each cluster are shown in their respective coloured area. ( C ) Heatmap representing the expression changes of top 30 miRNAs in cultured PHHs on days 1, 2, and 5. Red font colour indicate the miRNAs already associated with the functionality and lipid metabolism of PHHs. Int. J. Mol. Sci. 2019,20, 2910 16 of 20 Abbreviations CE cholesteryl ester CerS ceramide synthase DAG diacylglycerol ELOVL fatty acid elongase ER endoplasmic reticulum FA fatty acid FADS fatty acid desaturase FASN fatty acid synthase Gb3 globotriaosylceramide GCK glucokiase Glc/GalCer glucosyl/galactosylceramide GSL glycosphingolipid hLTR human liver total RNA HUFA highly unsaturated fatty acid LacCer lactosylceramide LCFA long-chain fatty acid miRNA microRNA MUFA monounsaturated fatty acid PC phosphatidylcholine PE phosphatidylethanolamine PCK1 phosphoenolpyruvate carboxykinase PHH primary human hepatocyte PI phosphatidylinositol PKLR liver-type pyruvate kinase PL phospholipid PS phosphatidylserine PUFA polyunsaturated fatty acid qPCR quantitative PCR RXRαretinoid X receptor alpha SCD stearoyl-CoA desaturase SFA saturated fatty acid SL sphingolipid SM sphingomyelin SMS sphingomyelin synthase TAG triacylglycerol UGCG UDP-glucose ceramide glucosyltransferase VLCFA very-long-chain fatty acid References 1. Sahi, J.; Grepper, S.; Smith, C. Hepatocytes as a tool in drug metabolism, transport and safety evaluations in drug discovery. Curr. Drug Discov. Technol. 2010,7, 188–198. [PubMed] 2. Kakisaka, K.; Cazanave, S.C.; Fingas, C.D.; Guicciardi, M.E.; Bronk, S.F.; Werneburg, N.W.; Mott, J.L.; Gores, G.J. Mechanisms of lysophosphatidylcholine-induced hepatocyte lipoapoptosis. AJP Gastrointest. Liver Physiol. 2012,302, G77–G84. [CrossRef] [PubMed] 3. Ling, J.; Lewis, J.; Douglas, D.; Kneteman, N.M.; Vance, D.E. Characterization of lipid and lipoprotein metabolism in primary human hepatocytes. Biochim. Biophys. Acta 2013 ,1831, 387–397. [CrossRef] [PubMed] 4. Gordillo, M.; Evans, T.; Gouon-Evans, V. Orchestrating liver development. Development 2015 ,142, 2094–2108. [CrossRef] [PubMed] 5. Schwartz, R.E.; Trehan, K.; Andrus, L.; Sheahan, T.P.; Ploss, A.; Duncan, S.A.; Rice, C.M.; Bhatia, S.N. Modeling hepatitis C virus infection using human induced pluripotent stem cells. Proc. Natl. Acad. Sci. USA 2012,109, 2544–2548. [CrossRef] [PubMed] Int. J. Mol. Sci. 2019,20, 2910 17 of 20 6. Westerink, W.M.A.; Schoonen, W.G.E.J. Cytochrome P450 enzyme levels in HepG2 cells and cryopreserved primary human hepatocytes and their induction in HepG2 cells. Toxicol. In Vitro 2007 ,21, 1581–1591. [CrossRef] [PubMed] 7. Michalopoulos, G. Liver regeneration. J. Cell. Physiol. 2007,213, 286–300. [CrossRef] 8. Elaut, G.; Henkens, T.; Papeleu, P.; Snykers, S.; Vinken, M.; Vanhaecke, T.; Rogiers, V. Molecular mechanisms underlying the dedifferentiation process of isolated hepatocytes and their cultures. Curr. Drug Metab. 2006 , 7, 629–660. [CrossRef] 9. Godoy, P.; Hewitt, N.J.; Albrecht, U.; Andersen, M.E.; Ansari, N.; Bhattacharya, S.; Bode, J.G.; Bolleyn, J.; Borner, C.; Böttger, J.; et al. Recent advances in 2D and 3D in vitro systems using primary hepatocytes, alternative hepatocyte sources and non-parenchymal liver cells and their use in investigating mechanisms of hepatotoxicity, cell signaling and ADME. Arch. Toxicol. 2013,87, 1315–1530. [CrossRef] 10. Godoy, P.; Hengstler, J.G.; Ilkavets, I.; Meyer, C.; Bachmann, A.; Müller, A.; Tuschl, G.; Mueller, S.O.; Dooley, S. Extracellular matrix modulates sensitivity of hepatocytes to fibroblastoid dedifferentiation and transforming growth factor β-induced apoptosis. Hepatology 2009,49, 2031–2043. [CrossRef] 11. Gieseck, R.L.; Hannan, N.R.F.; Bort, R.; Hanley, N.A.; Drake, R.A.L.; Cameron, G.W.W.; Wynn, T.A.; Vallier, L. Maturation of induced pluripotent stem cell derived hepatocytes by 3D-culture. PLoS ONE 2014 ,9, e86372. [CrossRef] [PubMed] 12. Foster, E.; You, J.; Siltanen, C.; Patel, D.; Haque, A.; Anderson, L.; Revzin, A. Heparin hydrogel sandwich cultures of primary hepatocytes. Eur. Polym. J. 2015,72, 726–735. [CrossRef] 13. Heidariyan, Z.; Ghanian, M.H.; Ashjari, M.; Farzaneh, Z.; Najarasl, M.; Rezaei Larijani, M.; Piryaei, A.; Vosough, M.; Baharvand, H. Efficient and cost-effective generation of hepatocyte-like cells through microparticle-mediateddeliveryofgrowthfactorsina3Dcultureof humanpluripotentstemcells. Biomaterials 2018,159, 174–188. [CrossRef] [PubMed] 14. Zhong, L.; Gou, J.; Deng, N.; Shen, H.; He, T.; Zhang, B.Q. Three-dimensional Co-culture of hepatic progenitor cells and mesenchymal stem cells in vitro and in vivo .Microsc. Res. Tech. 2015 ,78, 688–696. [CrossRef] [PubMed] 15. Kruitwagen, H.S.; Oosterhoff, L.A.; Vernooij, I.G.W.H.; Schrall, I.M.; van Wolferen, M.E.; Bannink, F.; Roesch, C.; van Uden, L.; Molenaar, M.R.; Helms, J.B.; et al. Long-term adult feline liver organoid cultures for disease modeling of hepatic steatosis. Stem Cell Rep. 2017,8, 822–830. [CrossRef] [PubMed] 16. Gijbels, E.; Vanhaecke, T.; Vinken, M. Establishment of sandwich cultures of primary human hepatocytes. In Methods in Molecular Biology; Springer: Berlin, Germany, 2019; Volume 1981, pp. 325–333. 17. Beigel, J.; Fella, K.; Kramer, P.J.; Kroeger, M.; Hewitt, P. Genomics and proteomics analysis of cultured primary rat hepatocytes. Toxicol. In Vitro 2008,22, 171–181. [CrossRef] 18. Heslop, J.A.; Rowe, C.; Walsh, J.; Sison-Young, R.; Jenkins, R.; Kamalian, L.; Kia, R.; Hay, D.; Jones, R.P.; Malik, H.Z.; et al. Mechanistic evaluation of primary human hepatocyte culture using global proteomic analysis reveals a selective dedifferentiation profile. Arch. Toxicol. 2017,91, 439–452. [CrossRef] 19. Kim, Y.; Lasher, C.D.; Milford, L.M.; Murali, T.M.; Rajagopalan, P. A comparative study of genome-wide transcriptional profiles of primary hepatocytes in collagen sandwich and monolayer cultures. Tissue Eng. Part C. Methods 2010,16, 1449–1460. [CrossRef] 20. Lasher, C.D.; Rajagopalan, P.; Murali, T.M. Discovering networks of perturbed biological processes in hepatocyte cultures. PLoS ONE 2011,6, e15247. [CrossRef] 21. Rowe, C.; Goldring, C.E.P.; Kitteringham, N.R.; Jenkins, R.E.; Lane, B.S.; Sanderson, C.; Elliott, V.; Platt, V.; Metcalfe, P.; Park, B.K. Network analysis of primary hepatocyte dedifferentiation using a shotgun proteomics approach. J. Proteome Res. 2010,9, 2658–2668. [CrossRef] 22. Lauschke, V.M.; Vorrink, S.U.; Moro, S.M.L.; Rezayee, F.; Nordling, Å.; Hendriks, D.F.G.; Bell, C.C.; Sison-Young, R.; Park, B.K.; Goldring, C.E.; et al. Massive rearrangements of cellular MicroRNA signatures are key drivers of hepatocyte dedifferentiation. Hepatology 2016,64, 1743–1756. [CrossRef] [PubMed] 23. Muro, E.; Atilla-Gokcumen, G.E.; Eggert, U.S. Lipids in cell biology: How can we understand them better? Mol. Biol. Cell 2014,25, 1819–1823. [CrossRef] [PubMed] 24. Zanger, U.M.; Schwab, M. Cytochrome P450 enzymes in drug metabolism: Regulation of gene expression, enzyme activities, and impact of genetic variation. Pharmacol. Ther. 2013 ,138, 103–141. [CrossRef] [PubMed] 25. Cai, S.-Y.; He, H.; Nguyen, T.; Mennone, A.; Boyer, J.L. Retinoic acid represses CYP7A1 expression in human hepatocytes and HepG2 cells by FXR/RXR-dependent and independent mechanisms. J. Lipid Res. 2010 ,51, 2265–2274. [CrossRef] [PubMed] Int. J. Mol. Sci. 2019,20, 2910 18 of 20 26. Lewi´n-ska, M.; Zelenko, U.; Merzel, F.; Grdadolnik, S.G.; Murray, J.C.; Rozman, D. Polymorphisms of CYP51A1 from cholesterol synthesis: Associations with birth weight and maternal lipid levels and impact on CYP51 protein structure. PLoS ONE 2013,8, e82554. 27. Kiamehr, M. Induced pluripotent stem cell-derived hepatocyte-like cells; the lipid status in differentiation, functionality, and de-differentiation of hepatic cells. Ph.D. Dissertation, Tampere University, Tampere, Finland, 2019. Available online: https://trepo.tuni.fi/handle/10024/104905 (accessed on 8 February 2019). 28. Baker, T.K.; Carfagna, M.A.; Gao, H.; Dow, E.R.; Li, Q.; Searfoss, G.H.; Ryan, T.P. Temporal gene expression analysis of monolayer cultured rat hepatocytes. Chem. Res. Toxicol. 2001 ,14, 1218–1231. [CrossRef] [PubMed] 29. Gault, C.R.; Obeid, L.M.; Hannun, Y.A. An overview of sphingolipid metabolism: From synthesis to breakdown. Adv. Exp. Med. Biol. 2010,688, 1–23. [PubMed] 30. Bartke, N.; Hannun, Y.A. Bioactive sphingolipids: Metabolism and function. J. Lipid Res. 2008 ,50, 91–96. [CrossRef] [PubMed] 31. Delgado, A.; Casas, J.; Llebaria, A.; Abad, J.L.; Fabrias, G. Inhibitors of sphingolipid metabolism enzymes. Biochim. Biophys. Acta - Biomembr. 2006,1758, 1957–1977. [CrossRef] [PubMed] 32. Jennemann, R.; Gröne, H.J. Cell-specific in vivo functions of glycosphingolipids: Lessons from genetic deletions of enzymes involved in glycosphingolipid synthesis. Prog. Lipid Res. 2013 ,52, 231–248. [CrossRef] 33. Cingolani, F.; Futerman, A.H.; Casas, J. Ceramide synthases in biomedical research. Chem. Phys. Lipids 2016 , 197, 25–32. [CrossRef] [PubMed] 34. Saddoughi, S.A.; Song, P.; Ogretmen, B. Roles of Bioactive Sphingolipids in Cancer Biology and Therapeutics. Lipids Health Dis. 2008,49, 413–440. 35. Mesicek, J.; Lee, H.; Feldman, T.; Jiang, X.; Skobeleva, A.; Berdyshev, E.V.; Haimovitz-Friedman, A.; Fuks, Z.; Kolesnick, R. Ceramide synthases 2, 5, and 6 confer distinct roles in radiation-induced apoptosis in HeLa cells. Cell. Signal. 2010,22, 1300–1307. [CrossRef] [PubMed] 36. Hannun, Y.A.; Luberto, C. Lipid metabolism: Ceramide transfer protein adds a new dimension. Curr. Biol. 2004,14, R163–R165. [CrossRef] [PubMed] 37. Li, Z.; Hailemariam, T.K.; Zhou, H.; Li, Y.; Duckworth, D.C.; Peake, D.A.; Zhang, Y.; Kuo, M.S.; Cao, G.; Jiang, X.C. Inhibition of sphingomyelin synthase (SMS) affects intracellular sphingomyelin accumulation and plasma membrane lipid organization. Biochim. Biophys. Acta-Mol. Cell Biol. Lipids 2007 ,1771, 1186–1194. [CrossRef] 38. Simons, K.; Gerl, M.J. Revitalizing membrane rafts: New tools and insights. Nat. Rev. Mol. Cell Biol. 2010 ,11, 688–699. [CrossRef] [PubMed] 39. Ishibashi, Y.; Kohyama-Koganeya, A.; Hirabayashi, Y. New insights on glucosylated lipids: Metabolism and functions. Biochim. Biophys. Acta-Mol. Cell Biol. Lipids 2013,1831, 1475–1485. [CrossRef] 40. Jensen-Urstad, A.P.L.; Semenkovich, C.F. Fatty acid synthase and liver triglyceride metabolism: Housekeeper or messenger? Biochim. Biophys. Acta-Mol. Cell Biol. Lipids 2012,1821, 747–753. [CrossRef] 41. Ntambi, J.M.; Miyazaki, M. Regulation of stearoyl-CoA desaturases and role in metabolism. Prog. Lipid Res. 2004,43, 91–104. [CrossRef] 42. Jakobsson, A.; Westerberg, R.; Jacobsson, A. Fatty acid elongases in mammals: Their regulation and roles in metabolism. Prog. Lipid Res. 2006,45, 237–249. [CrossRef] 43. Ntambi, J.M. Regulation of stearoyl-CoA desaturase by polyunsaturated fatty acids and cholesterol. J. Lipid Res. 1999,40, 1549–1558. [PubMed] 44. Park, J.W.; Park, W.J.; Futerman, A.H. Ceramide synthases as potential targets for therapeutic intervention in human diseases. Biochim. Biophys. Acta-Mol. Cell Biol. Lipids 2014,1841, 671–681. [CrossRef] [PubMed] 45. Mullen, T.D.; Hannun, Y.A.; Obeid, L.M. Ceramide synthases at the centre of sphingolipid metabolism and biology. Biochem. J. 2012,441, 789–802. [CrossRef] [PubMed] 46. Adada, M.; Luberto, C.; Canals, D. Inhibitors of the sphingomyelin cycle: Sphingomyelin synthases and sphingomyelinases. Chem. Phys. Lipids 2016,197, 45–59. [CrossRef] [PubMed] 47. Kim, W.J.; Okimoto, R.A.; Purton, L.E.; Goodwin, M.; Haserlat, S.M.; Dayyan, F.; Sweetser, D.A.; Mcclatchey, A.I.; Bernard, O.A.; Look, A.T.; et al. Mutations in the neutral sphingomyelinase gene Smpd3 implicate the ceramide pathway in human leukemias. Blood 2008 ,111, 4716–4722. [CrossRef] [PubMed] 48. D’Angelo, G.; Capasso, S.; Sticco, L.; Russo, D. Glycosphingolipids: Synthesis and functions. FEBS J. 2013 , 280, 6338–6353. [CrossRef] [PubMed] Int. J. Mol. Sci. 2019,20, 2910 19 of 20 49. Lee, J.M.; Lee, H.; Kang, S.B.; Park, W.J. Fatty acid desaturases, polyunsaturated fatty acid regulation, and biotechnological advances. Nutrients 2016,8, 23. [CrossRef] [PubMed] 50. Jump, D.B. Mammalian fatty acid elongases. Methods Mol. Biol. 2009,579, 375–389. 51. Duplus, E.; Forest, C. Is there a single mechanism for fatty acid regulation of gene transcription? Biochem. Pharmacol. 2002,64, 893–901. [CrossRef] 52. Currie, E.; Schulze, A.; Zechner, R.; Walther, T.C.; Farese, R.V. Cellular fatty acid metabolism and cancer. Cell Metab. 2013,18, 153–161. [CrossRef] 53. Finelli, C.; Tarantino, G. Have guidelines addressing physical activity been established in nonalcoholic fatty liver disease? World J. Gastroenterol. 2012,18, 6790–6800. [CrossRef] [PubMed] 54. Fraczek, J.; Bolleyn, J.; Vanhaecke, T.; Rogiers, V.; Vinken, M. Primary hepatocyte cultures for pharmaco-toxicological studies: At the busy crossroad of various anti-dedifferentiation strategies. Arch. Toxicol. 2013,87, 577–610. [CrossRef] 55. Yang, Z.; Cappello, T.; Wang, L. Emerging role of microRNAs in lipid metabolism. Acta Pharm. Sin. B 2015 ,5, 145–150. [CrossRef] [PubMed] 56. Zhang, M.; Sun, W.; Zhou, M.; Tang, Y. MicroRNA-27a regulates hepatic lipid metabolism and alleviates NAFLD via repressing FAS and SCD1. Sci. Rep. 2017,7, 1–10. [CrossRef] [PubMed] 57. Nov á k, J.; Olejn í ˇckov á , V.; Tk á ˇcov á , N.; Santulli, G. Mechanistic role of microRNAs in coupling lipid metabolism and atherosclerosis. In Advances in Experimental Medicine and Biology; Santulli, G., Ed.; Springer: Cham, Switzerland, 2015; Volume 887, pp. 79–100. ISBN 978-3-319-22379-7. 58. Takagi, S.; Nakajima, M.; Kida, K.; Yamaura, Y.; Fukami, T.; Yokoi, T. MicroRNAs regulate human hepatocyte nuclear factor 4alpha, modulating the expression of metabolic enzymes and cell cycle. J. Biol. Chem. 2010 , 285, 4415–4422. [CrossRef] [PubMed] 59. Loyer, X.; Paradis, V.; H é nique, C.; Vion, A.C.; Colnot, N.; Guerin, C.L.; Devue, C.; On, S.; Scetbun, J.; Romain, M.; et al. Liver microRNA-21 is overexpressed in non-alcoholic steatohepatitis and contributes to the disease in experimental models by inhibiting PPARαexpression. Gut 2016,65, 1882–1894. [CrossRef] 60. Goodwin, B.; Jones, S.A.; Price, R.R.; Watson, M.A.; McKee, D.D.; Moore, L.B.; Galardi, C.; Wilson, J.G.; Lewis, M.C.; Roth, M.E.; et al. A regulatory cascade of the nuclear receptors FXR, SHP-1, and LRH-1 represses bile acid biosynthesis. Mol. Cell 2000,6, 517–526. [CrossRef] 61. Oda, Y.; Nakajima, M.; Tsuneyama, K.; Takamiya, M.; Aoki, Y.; Fukami, T.; Yokoi, T. Retinoid X receptor α in human liver is regulated by miR-34a. Biochem. Pharmacol. 2014,90, 179–187. [CrossRef] 62. Rodgers, J.T.; Puigserver, P. Fasting-dependent glucose and lipid metabolic response through hepatic sirtuin 1. Proc. Natl. Acad. Sci. USA 2007,104, 12861–12866. [CrossRef] 63. Kim, H.R.; Roe, J.S.; Lee, J.E.; Cho, E.J.; Youn, H.D. P53 regulates glucose metabolism by miR-34a. Biochem. Biophys. Res. Commun. 2013,437, 225–231. [CrossRef] 64. Ye, X.; Li, M.; Hou, T.; Gao, T.; Zhu, W.; Yang, Y. Sirtuins in glucose and lipid metabolism. Oncotarget 2017 ,8, 1845–1859. [CrossRef] [PubMed] 65. Reyes,R.K.; Motiwala,T.; Jacob,S.T.Regulationofglucose metabolisminhepatocarcinogenesisbyMicroRNAs. Gene Expr. 2014,16, 85–92. [CrossRef] [PubMed] 66. Wang, B.; Hsu, S.H.; Frankel, W.; Ghoshal, K.; Jacob, S.T. Stat3-mediated activation of microRNA-23a suppresses gluconeogenesis in hepatocellular carcinoma by down-regulating Glucose-6-phosphatase and peroxisome proliferator-activated receptor gamma, coactivator 1 alpha. Hepatology 2012 ,56, 186–197. [CrossRef] [PubMed] 67. Ji, J.; Zhang, J.; Huang, G.; Qian, J.; Wang, X.; Mei, S. Over-expressed microRNA-27a and 27b influence fat accumulation and cell proliferation during rat hepatic stellate cell activation. FEBS Lett. 2009 ,583, 759–766. [CrossRef] [PubMed] 68. Shirasaki, T.; Honda, M.; Shimakami, T.; Horii, R.; Yamashita, T.; Sakai, Y.; Sakai, A.; Okada, H.; Watanabe, R.; Murakami, S.; et al. MicroRNA-27a regulates lipid metabolism and inhibits hepatitis C virus replication in human hepatoma cells. J. Virol. 2013,87, 5270–5286. [CrossRef] [PubMed] 69. Ahn, J.; Lee, H.; Jung, C.H.; Ha, T. Lycopene inhibits hepatic steatosis via microRNA-21-induced downregulation of fatty acid-binding protein 7 in mice fed a high-fat diet. Mol. Nutr. Food Res. 2012 ,56, 1665–1674. [CrossRef] [PubMed] 70. Kida, K.; Nakajima, M.; Mohri, T.; Oda, Y.; Takagi, S.; Fukami, T.; Yokoi, T. PPAR α is regulated by miR-21 and miR-27b in human liver. Pharm. Res. 2011,28, 2467–2476. [CrossRef] Int. J. Mol. Sci. 2019,20, 2910 20 of 20 71. Fern á ndez-Alvarez, A.; Soledad Alvarez, M.; Gonzalez, R.; Cucarella, C.; Muntan é , J.; Casado, M. Human SREBP1c expression in liver is directly regulated by Peroxisome Proliferator-activated Receptor α (PPAR α ). J. Biol. Chem. 2011,286, 21466–21477. [CrossRef] 72. Fan, J.; Li, H.; Nie, X.; Yin, Z.; Zhao, Y.; Chen, C.; Wen Wang, D. MiR-30c-5p ameliorates hepatic steatosis in leptin receptor-deficient (db/db) mice via down-regulating FASN. Oncotarget 2017 ,8, 13450–13463. [CrossRef] 73. Irani, S.; Hussain, M.M. Role of microRNA-30c in lipid metabolism, adipogenesis, cardiac remodeling and cancer. Curr. Opin. Lipidol. 2015,26, 139–146. [CrossRef] 74. Esau, C.; Davis, S.; Murray, S.F.; Yu, X.X.; Pandey, S.K.; Pear, M.; Watts, L.; Booten, S.L.; Graham, M.; McKay, R.; et al. miR-122 regulation of lipid metabolism revealed by in vivo antisense targeting. Cell Metab. 2006,3, 87–98. [CrossRef] [PubMed] 75. Poy, M.N.; Spranger, M.; Stoffel, M. microRNAs and the regulation of glucose and lipid metabolism. Diabetes, Obes. Metab. 2007,9, 67–73. [CrossRef] 76. Ståhlman, M.; Ejsing, C.S.; Tarasov, K.; Perman, J.; Bor é n, J.; Ekroos, K. High-throughput shotgun lipidomics by quadrupole time-of-flight mass spectrometry. J. Chromatogr. B Anal. Technol. Biomed. Life Sci. 2009 ,877, 2664–2672. [CrossRef] 77. Kiamehr, M.; Viiri, L.E.; Vihervaara, T.; Koistinen, K.M.; Hilvo, M.; Ekroos, K.; Kakela, R.; Aalto-Setala, K. Lipidomic profiling of patient-specific iPSC-derived hepatocyte-like cells. DMM Dis. Model. Mech. 2017 ,10, 1141–1153. [CrossRef] [PubMed] 78. Heiskanen, L.A.; Suoniemi, M.; Ta, H.X.; Tarasov, K.; Ekroos, K. Long-Term Performance and Stability of Molecular Shotgun Lipidomic Analysis of Human Plasma Samples. Anal. Chem. 2013 ,85, 8757–8763. [CrossRef] 79. Ekroos, K.; Ejsing, C.S.; Bahr, U.; Karas, M.; Simons, K.; Shevchenko, A. Charting molecular composition of phosphatidylcholines by fatty acid scanning and ion trap MS3 fragmentation. J. Lipid Res. 2003 ,44, 2181–2192. [CrossRef] 80. Ekroos, K.; Chernushevich, I.V.; Simons, K.; Shevchenko, A. Quantitative profiling of phospholipids by multiple precursor ion scanning on a hybrid quadrupole time-of-flight mass spectrometer. Anal. Chem. 2002 , 74, 941–949. [CrossRef] 81. Merrill, A.H.; Sullards, M.C.; Allegood, J.C.; Kelly, S.; Wang, E. Sphingolipidomics: High-throughput, structure-specific, and quantitative analysis of sphingolipids by liquid chromatography tandem mass spectrometry. Methods 2005,36, 207–224. [CrossRef] [PubMed] 82. Ejsing, C.S.; Duchoslav, E.; Sampaio, J.; Simons, K.; Bonner, R.; Thiele, C.; Ekroos, K.; Shevchenko, A. Automated identification and quantification of glycerophospholipid molecular species by multiple precursor ion scanning. Anal. Chem. 2006,78, 6202–6214. [CrossRef] 83. Kiamehr, M.; Alexanova, A.; Viiri, L.E.; Heiskanen, L.; Vihervaara, T.; Kauhanen, D.; Ekroos, K.; Laaksonen, R.; Käkelä, R.; Aalto-Setälä, K. hiPSC-derived hepatocytes closely mimic the lipid profile of primary hepatocytes: A future personalised cell model for studying the lipid metabolism of the liver. J. Cell. Physiol. 2019 ,234, 3744–3761. [CrossRef] 84. Bolstad, B.M.; Irizarry, R.A.; Astrand, M.; Speed, T.P. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 2003 ,19, 185–193. [CrossRef] [PubMed] 85. Irizarry, R.A.; Bravo, H.C.; Irizarry, R.A.; Irizarry, R.; Hobbs, B.; Collin, F.; Beazer-Barclay, Y.; Antonellis, K.; Scherf, U.; Speed, T.; et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 2003,4, 249–264. [CrossRef] [PubMed] © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).