Deciphering the cell type-specific and zonal distribution of drug-metabolizing enzymes, transporters, and transcription factors in livers of mice using single-cell transcriptomics

Joe Jongpyo Lim; Curtis Dean Klaassen; Julia Yue Cui

doi:10.1016/j.dmd.2024.100029

. 2024 Dec 12;53(2):100029. doi: 10.1016/j.dmd.2024.100029

Deciphering the cell type-specific and zonal distribution of drug-metabolizing enzymes, transporters, and transcription factors in livers of mice using single-cell transcriptomics

Joe Jongpyo Lim ^1,², Curtis Dean Klaassen ^3,^∗∗, Julia Yue Cui ^1,^2,^∗

PMCID: PMC13095463 PMID: 39919554

Abstract

The liver contains multiple cell types, including resident cell types and immune cells. The liver is also categorized into 3 zones: periportal (zone 1), midzonal (zone 2), and centrilobular (zone 3). The goal of this study was to characterize the distribution of drug-processing genes (DPGs) in mouse liver using published single-cell and nuclei transcriptomic datasets, which were subjected to zonal deconvolution. Filtering, normalization, clustering, and differential expression analyses were performed using Seurat V5 in R. Hepatocytes were assigned to 3 zones based on known zonal markers and validated with published spatial transcriptomics data. Among the 195 DPGs profiled, most were expressed highest in hepatocytes (61.3%). Interestingly, certain DPGs were expressed most highly in nonparenchymal cells, such as in cholangiocytes (11.2%, eg, carboxylesterase [Ces] 2e, Ces2g), endothelial cells (7.2%, eg, aldo-keto reductase [Akr] 1c19, Akr1e1), Kupffer cells (5.3%, eg, Akr1a1, Akr1b10), stellate cells (5.1%, eg, retinoic acid receptor [Rar] α, Rarβ), myofibroblasts (2.9%, RAR-related orphan receptor [Rar] α), and a few were expressed in immune cell types. In hepatocytes, 72.4% of phase-I enzymes were enriched in zone 3. Phase-II conjugation enzymes such as UDP-glucuronosyltransferases (75%) were enriched in zone 3, whereas sulfotransferases (40%) were enriched in zone 1. Hepatic xenobiotic transporters were enriched in zone 3. The xenobiotic biotransformation-regulating transcription factors were enriched in zone 3 hepatocytes. The enrichment of DPGs in liver cell types, including non-parenchymal cells and zone 1 hepatocytes, may serve as an additional repertoire for xenobiotic biotransformation.

Significance Statement

Our study is among the first to systematically characterize the baseline mRNA enrichment of important drug-processing genes in different cell types and zones in the liver. This finding will aid in further understanding the mechanisms of chemical-induced liver injury with improved resolution and precision.

Keywords: Drug metabolizing enzymes, Liver cell types, Single cell RNA-sequencing, Systems biology, Spatial deconvolution

1. Introduction

The liver is a major organ for the distribution, metabolism, and excretion of various xenobiotics and intermediary metabolites (Klaassen, 2018). The liver consists of various cell types, each with unique functions and characteristics. Hepatocytes are the most abundant and extensively studied cells, making up approximately 75% of the liver mass and responsible for most of its metabolic and synthetic activities in adult liver (Duncan et al, 2009). Hepatocytes express a wide array of drug-metabolizing enzymes and transporters, collectively known as drug-processing genes (DPGs), which play a crucial role in the pharmacokinetics and toxicokinetics of chemicals (Sheweita, 2000). At the transcriptional level, DPGs are regulated by various nuclear receptors and other xenobiotic-sensing transcription factors in the liver, serving as a compensatory mechanism in response to xenobiotic exposure (Aleksunes and Klaassen, 2012; Li et al, 2016).

In addition to hepatocytes, the liver contains various other cell types. Cholangiocytes are the ductal epithelial cells; endothelial cells line the hepatic sinusoids; stellate cells are the perisinusoidal fat-storing mesenchymal cells; myofibroblasts regulate metabolic and immunological processes; and Kupffer cells serve as the resident macrophage population in the liver (Ding et al, 2016). Importantly, hepatocytes are not the only cells in the liver that express DPGs. Other cell types, such as cholangiocytes, endothelial cells, stellate cells, myofibroblasts, Kupffer cells, and circulating immune cells, may also metabolize and transport various substances. Their role in liver function and disease has been increasingly recognized in recent years (Bell et al, 2020; Lim et al, 2024). These nonparenchymal cells are crucial for maintaining liver homeostasis and integrity, as well as modulating the inflammatory, fibrotic, and regenerative responses to liver injury (van Berkel, 1979; Malik et al, 2002; Seo and Jeong, 2016). Moreover, they can interact with hepatocytes and influence the hepatocyte DPG expression and activity, either directly or indirectly, through cell-cell contact, paracrine signaling, or extracellular matrix remodeling (Underhill and Khetani, 2018; Kulsharova and Kurmangaliyeva, 2021; Natarajan et al, 2021).

In addition to cell type specificity, the liver is divided into 3 zones: periportal (zone 1), midzonal (zone 2), and centrilobular (zone 3) with distinct metabolic capacities (Cunningham and Porat-Shliom, 2021; Paris and Henderson, 2022). For example, CYP2E1 has been shown to be expressed highest in zone 3, leading to greater acetaminophen-induced hepatotoxicity in this area (Yoon et al, 2016). There is a lack of systematic characterization of the cell type and zonal distribution of all DPGs and their regulatory transcription factors in the liver. Characterizing these distributions with single-cell resolution and with zonal specificity is important for further understanding the metabolic heterogeneity within the zonal architecture and disease mechanisms, as well as both precision medicine and precision environmental health. Therefore, the goal of the present study was to use single-cell transcriptomics and spatial transcriptomics to determine the cell type-specific and zonal-specific distribution of DPGs and their regulatory transcription factors, using a published dataset in mouse liver (Guilliams et al, 2022).

2. Materials and methods

2.1. Single-cell RNA/nuclei sequencing data processing

Single-cell and single nuclei RNA sequencing (sc/sn RNA-seq) data from 6–12 week-old male and female C57BL/6 mouse livers were sourced from the Gene Expression Omnibus database: GSE192742 (Guilliams et al, 2022). The dataset includes 3 types of digestion methods: in vivo (retrograde enzymatic perfusion), ex vivo (mechanical and enzymatic dissociation without perfusion), and nuclei (isolated nuclei from flash-frozen tissue). Libraries were constructed using the 3` Gel Bead and Library Kit (10X Genomics). Reads were aligned to the mouse mm10 reference genome using CellRanger version 3.1.0. Data processing and analysis were performed in R version 4.3.1 unless noted otherwise. Ambient RNA was removed using the R package FastCAR version 0.1.0 (Berg et al, 2023). Outliers were filtered out based on library size, number of expressed genes, and mitochondrial proportion following the procedures described previously (Lun et al, 2016).

Unnormalized liver scRNA (in vivo and ex vivo) and nuclei sequencing count files were read into R using Seurat V5 (Hao et al, 2024). The count data for each digestion method were normalized and sc/sn RNA expression data were integrated using canonical correlation analysis with default Seurat parameters. Clusters were labeled into cell types based on marker genes identified using the FindAllMarkers function. Gene expression values were normalized using SCTransform (Hafemeister and Satija, 2019) and averaged to produce cell type-specific mean expression. DPGs and transcription factors were curated from previous knowledge bases (Parkinson et al, 2019) (Supplemental Tables 1–5) and were used to generate average DPG expression for each cell type. DPGs whose expression was highly sparse (ie, DPGs expressed < 10% in a given cell type) were excluded from further analysis and were assigned zeros.

2.2. Spatial transcriptomics data processing

Visium spatial transcriptomics data were downloaded from a previous study (Guilliams et al, 2022). The data were imported into R using Seurat V5 (Hao et al, 2024) and were processed according to the spatial transcriptomics analysis workflow (https://satijalab.org/seurat/articles/spatial_vignette). Normalization was performed using SCTransform (Hafemeister and Satija, 2019). Spot zonation labels from the original publication (Guilliams et al, 2022) were used to ensure reproducibility and validation of the sc/sn RNA sequencing zonation inference.

2.3. Zonation inference of hepatocytes

Hepatocyte-specific gene expression was extracted from the gene expression matrix with cell types labeled. Subclustering of hepatocyte data was performed using Seurat V5 (Hao et al, 2024). The raw count reads were transformed as follows:

n_{i j} = \frac{c_{i j}}{\sum_{j = 1}^{N} c_{i j}}

r_{i j} = \frac{n_{i j}}{1 / M \sum_{i = 1}^{M} n_{i j}}

s_{i j} = \frac{r_{i j} σ_{i}}{m e d i a n (r_{j})}

In which $i$ and $j$ represent the genes and cells in the single-cell gene expression matrix; $n$ is the count-normalized value ( $i$ by $j$ matrix); $N$ is the total number of cells; $c$ is the integer count value of reads; $r$ is the relative expression value; $M$ is the number of genes; $s$ is the final transformed expression value; and $σ$ is the standard deviation of the gene expression.

The approach in the present study identifies hepatocytes as periportal or centrilobular based on the degree of expression of zonal marker genes within hepatocyte subclusters. The transformed expression space in this enables the comparison of the expression of marker genes based on the gradient and distribution. A 75-percentile threshold was used to determine the relative expression levels of periportal (zone 1) and centrilobular (zone 3) hepatocyte markers. As the threshold increases, the number of cells identified as periportal or centrilobular hepatocytes is expected to decrease, while the number of cells classified with transformed expression between the thresholds (defined as midzonal) is expected to increase. In this study, the total number of hepatocytes in each inferred zone was as follows: 6775 periportal, 11,316 midzonal, and 8354 centrilobular, corresponding to 25.6% periportal, 42.8% midzonal, and 31.6% centrilobular hepatocytes relative to the total number of hepatocytes. Gene expression can vary within cell clusters, and a larger number of cells can provide a more accurate representation of gene expression within these clusters. Benchmarking studies (Liu et al, 2023) suggest that a few hundred cells per cluster is optimal, though the number can be as low as 50 cells per cluster in some analyses. In this study, subclustering analysis identified between 160 and 917 cells per hepatocyte subcluster, which were used for further analyses, including the inference of zonal identities.

Differential gene expression analysis was conducted using the FindAllMarker function, comparing inferred periportal and centrilobular hepatocytes in Seurat V5 (Hao et al, 2024) with default parameters (Bonferroni-adjusted P-value < 0.05). DPGs were matched with the differentially expressed genes, and the average fold change between periportal and centrilobular hepatocytes was calculated. Differentially expressed DPGs with a fold change in periportal or centrilobular hepatocytes > 1.1 in either periportal or centrilobular were considered enriched. Differential gene expression analysis was conducted using the FindAllMarker function comparing inferred periportal and centrilobular hepatocytes in Seurat V5 (Hao et al, 2024) with default parameters (Bonferroni-adjusted P-value < .05).

The inferred hepatocyte zones were validated with mouse liver spatial transcriptomics data by calculating the overlap proportion of differentially expressed DPGs in the sc/sn RNA sequencing and spatial transcriptomics data. Average DPG expression profiles in resident liver cells were merged with the zonation-inferred hepatocyte results and plotted as heatmaps using ComplexHeatmap version 2.16.0 (Gu et al, 2016; Gu, 2022). All other plots were generated using ggplot2 version 3.4.4.

3. Results

3.1. Inclusion of multiple digestion methods for sc/sn RNA-Seq data analysis

Different digestion methods, as shown in Table 1, yield varying proportions of cell types (Andrews et al, 2022; Van Melkebeke et al, 2024). Ex vivo isolation (mechanical and enzymatic dissociation) increases the proportion of non-parenchymal cell types, whereas in vivo isolation (perfusion with enzymatic dissociation) and hepatic nuclei isolation result in higher proportions of hepatocytes, more accurately reflecting the biological composition of the liver. To ensure accuracy in cell representation and enhance data robustness, all three digestion methods (in vivo, ex vivo, and nuclei) were used, resulting in 96,066, 71,162, and 18,666 cells, respectively, in total (Table 1). The resulting cell type-specific RNA expression profiles were integrated into a single dataset. Most hepatocytes were obtained using the in vivo method, followed by the nuclei digestion method. The in vivo method also yielded most endothelial cells and cholangiocytes followed by the ex vivo digestion method. The nuclei isolation method produced the most stellate cells and myofibroblasts, followed by the in vivo digestion method. Most Kupffer cells were obtained from the in vivo method, followed by the ex vivo digestion method. Other immune cell types in the liver (B cells, T cells, natural killer [NK] cells, dendritic cells (DCs), monocyte-derived macrophages [MDMs], and neutrophils) were primarily obtained using the ex vivo method, followed by the in vivo digestion method.

Table 1.

Number of cells in each labeled cell type

Cell type	Number				Proportion by total cells			Proportion by method
Cell type	In vivo	Ex vivo	Nuclei	Total	In vivo	Ex vivo	Nuclei	In vivo	Ex vivo	Nuclei
Hepatocyte	14,041	1531	10,832	26,404	0.53	0.06	0.41	0.15	0.02	0.58
Endothelial	36,473	11,367	2310	50,150	0.73	0.23	0.05	0.38	0.16	0.12
Cholangiocyte	804	218	10	1032	0.78	0.21	0.01	0.01	0.00	0.00
Stellate	1297	-	1854	3151	0.41	0.00	0.59	0.01	0.00	0.10
Myofibroblast	248	187	2797	3232	0.08	0.06	0.87	0.00	0.00	0.15
Kupffer	24,134	14,471	623	39,928	0.60	0.36	0.02	0.25	0.20	0.03
B cell	2997	3282	116	6395	0.47	0.51	0.02	0.03	0.05	0.01
T cell	2331	4515	68	6914	0.34	0.65	0.01	0.02	0.06	0.00
CD8	1021	1812	4	2837	0.36	0.64	0.00	0.01	0.03	0.00
NK	2054	2883	1	4938	0.42	0.58	0.00	0.02	0.04	0.00
cDC	2882	7996	34	10,912	0.26	0.73	0.00	0.03	0.11	0.00
pDC	3048	3361	-	6409	0.48	0.52	0.00	0.03	0.05	0.00
MDM	3543	16999	15	20,557	0.17	0.83	0.00	0.04	0.24	0.00
Neutrophil	1193	2540	2	3735	0.32	0.68	0.00	0.01	0.04	0.00
Sum	96,066	71,162	18,666	186,594

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3.2. Cell type identification using known marker genes

Each cell type in the mouse liver was identified using sc/sn RNA-seq. Clustering of sc/sn RNA gene expression profiles revealed the major resident liver cell types: hepatocytes, cholangiocytes, endothelial cells, stellate cells, myofibroblasts, and Kupffer cells. Additionally, immune cells such as B cells, T cells, CD8+ T cells, NK cells, conventional DCs (cDCs), plasmacytoid DCs (pDCs), MDMs, and neutrophils were identified as circulating cell types that reside in the liver (Fig. 1A). The cell clusters were labeled using well-established cell type markers (Fig. 1B). These known marker genes for each liver cell type are detailed below and are uniquely enriched in the data:

Fig. 1 — Clustering of single cell and single nuclei RNA sequencing of the mouse liver. (A) Clustering and cell type identification from sc/sn RNA sequencing (B) Average expression of marker genes used to label cell types of the sc/sn RNA sequencing data. CD8, CD8+ T cell; Mig.cDC, migratory conventional dendritic cell; NKT cell: natural killer T cell; pDC, plasmacytoid dendritic cell.

Compared with other cell types in the liver, alcohol dehydrogenase 1 (Adh1) (Ito et al, 1987) is known to be enriched in hepatocytes. Platelet and endothelial adhesion molecule 1 (Pecam1) (Bruggisser et al, 2020) and a cluster of differentiation (Cd) 38 (Zhu et al, 2020) are enriched in endothelial cells. Epithelial cell adhesion molecule (Epcam) (Tanimizu et al, 2021) is enriched in cholangiocytes. Collagen type III α 1 chain (Col3a1) (Ai et al, 2022; Bogomolova et al, 2024) is enriched in both stellate cells and hepatic myofibroblasts. Desmin (Des), lecithin retinol acyltransferase (Lrat), and elastin (Eln) (Penz-Österreicher et al, 2011) are used to distinguish stellate cells and ., respectively, from other cell types. Adhesion protein G-coupled receptor E1 (Adgre1, F4/80) (Blériot et al, 2021) and CD5 molecule-like (Cd5l) (Sakai et al, 2019) are enriched in Kupffer cells, which have a moderate expression of Cd38 (Boslett et al, 2018).

For the circulating immune cell types residing in the liver, membrane-spanning 4-domains (Ms4) A1 (Liang and Tedder, 2001) are enriched in B cells. Cd3e (Andreatta et al, 2021) is enriched in T cells, and Cd8a is also enriched in CD8 T cells (Deng et al, 2021). Granzyme A (Gzma) (Fehniger et al, 2007) is enriched in NK cells. The members of the RAS oncogene family (Rab7b) (Jirmo et al, 2023) and sialic acid-binding Ig-like lectin H (Siglech) (Zhang et al, 2006) are enriched in cDCs and pDCs, respectively. Ms4a6c (Sanyal et al, 2017) and C-type lectin domain family 4 (Clec4a3) (Okada et al, 2020) are enriched in MDMs. S100 calcium-binding proteins (S100a8 and S100a9) (Sprenkeler et al, 2022) are enriched in neutrophils.

3.3. Systematic characterization of the zonal distribution of DPGs in hepatocytes

The sc/sn RNA-seq data from hepatocytes were further analyzed to infer the zonal distribution of gene expression (see Materials and Methods). A series of transformations were applied to systematically distinguish the gene expression profiles in hepatocytes at the periphery and middle of the lobule (ie, periportal and centrilobular). Serine dehydratase (Sds), cytochrome P450 (Cyp) 2f2, histidase (Hal), hydroxysteroid 17-β dehydrogenase 13 (Hsd17b13), and aldehyde dehydrogenase (Aldh) 1b1 were used as markers for periportal hepatocytes (Hildebrandt et al, 2021). Glutamate-ammonia ligase (Glul, glutamine synthetase [GS]), ornithine aminotransferase (Oat), T-box transcription factor 3 (Tbx3), Cyp2e1, and Cyp2a5 were used as markers for centrilobular hepatocytes (Zhao et al, 2019; Hildebrandt et al, 2021). Expression of the marker genes showed a gradual increase or decrease in each zone, with the highest expression of the markers for the respective spatial zone having the highest expression and a marked difference in fold change (Fig. 2 and Table 2). Subsequently, the spatial zones of hepatocytes were inferred and labeled (Supplemental Fig. 1A) as periportal, midzonal, and centrilobular based on the expression gradient of the marker genes. The inference and identification of hepatocyte zones by each digestion method showed little difference (Supplemental Fig. 1B).

Fig. 2 — Visualization of gene-enriched periportal and centrilobular hepatocytes. Normalized expression values of markers enriched in periportal or centrilobular hepatocytes. Colors in blue and yellow represent centrilobular and periportal markers, respectively.

Table 2.

Marker genes used to infer hepatocyte zones and average marker gene expression

Zone	Marker	Average expression (SCTransform-normalized)			Fold change
Zone	Marker	Periportal	Midzonal	Centrilobular	P/C	C/P
Periportal	Sds	2.38	1.55	0.17	14.20	0.07
Periportal	Cyp2f2	2.59	1.33	0.25	10.44	0.10
Periportal	Hal	3.09	1.92	0.50	6.14	0.16
Periportal	Hsd17b13	1.70	0.84	0.22	7.56	0.13
Periportal	Aldh1b1	0.37	0.26	0.02	23.46	0.04
Centrilobular	Glul	0.20	0.95	2.97	0.07	14.51
Centrilobular	Oat	0.14	0.39	1.94	0.07	14.01
Centrilobular	Tbx3	0.07	0.26	0.82	0.09	11.23
Centrilobular	Cyp2e1	1.48	3.71	10.42	0.14	7.03
Centrilobular	Cyp2a5	0.10	0.30	1.43	0.07	14.25

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The DPGs include various phase-I and -II drug-metabolizing enzymes, transporters, as well as transcription factors as listed in Supplemental Tables 1–4. The mean expression of all DPGs across liver cell types is described in Supplemental Table 5. The gene expression of periportal and centrilobular hepatocytes was calculated to determine their spatial distribution within hepatocytes among the 3 different zones. Periportal hepatocytes were enriched in genes involved in ATP synthesis, aerobic respiration, oxidative phosphorylation, and energy metabolism (Fig. 3A). In contrast, centrilobular hepatocytes were enriched in genes related to fatty acid, xenobiotic, and steroid metabolism (Fig. 3B). These findings from our inferred spatial hepatocyte zones align with previous studies on liver metabolism, indicating that periportal hepatocytes specialize in oxidative energy metabolism functions, whereas centrilobular hepatocytes are primarily involved in xenobiotic and lipid metabolism (Berndt et al, 2018; Ben-Moshe et al, 2019; Chen et al, 2023).

Fig. 3 — Gene ontology enrichment of spatially-resolved hepatocytes. (A) Top 5 gene ontology (GO) terms enriched in periportal hepatocytes. (B) Top 5 GO terms enriched in centrilobular hepatocytes. The dotted line shows the statistical significance threshold at false discovery rate (FDR)-adjusted P at .05. -log₁₀ transformation was applied to the FDR-adjusted P-value on the x-axis to sort statistical significance in decreasing order (ie, a larger transformed value indicates a lower P-value).

Previously, methods such as gradient centrifugation (Panin and Usynin, 1987; Ölander et al, 2021) and zonal antibody labeling (Ben-Moshe et al, 2019) have been used to separate periportal and centrilobular hepatocytes. Recently, spatial transcriptomics, which is a slide-based technique that detects RNA and protein expression using probes targeting the transcriptome and antibodies, has enabled a more direct assessment of liver zonation (Hildebrandt et al, 2021). However, spatial transcriptomics methods are limited by the number of genes detected compared with sc/sn RNA-seq (Williams et al, 2022). To validate the distribution of DPGs in periportal and centrilobular hepatocytes inferred from sc/sn RNA-seq, spatial transcriptomics data were used, where hepatic lobules were identified (Guilliams et al, 2022). The DPGs enriched in either periportal or centrilobular hepatocytes inferred from the sc/sn RNA-Seq data were compared with zonation-labeled spatial transcriptomic data (Supplemental Fig. 1C). Overall, compared with the spatial transcriptomics data, 85.00% and 86.36% of DPGs in the sc/sn RNA-seq data were also enriched in periportal and centrilobular hepatocytes, respectively, with an overall agreement of 86.15% (Supplemental Fig. 1D).

3.4. Phase-I drug-metabolizing enzymes

Cytochrome P450s (Cyp) are essential enzymes for the biotransformation of both xenobiotics and endobiotics. Members of the Cyp1, Cyp2, and Cyp3 families are generally considered to be important for xenobiotic biotransformation (Zanger and Schwab, 2013), whereas the Cyp4 family is mainly involved in fatty acid metabolism (Edson and Rettie, 2013). In the present study, 49 Cyps are expressed in at least one cell type in the liver. Figure 4 describes the distribution of Cyps across various liver cell types based on the sc/sn RNA-Seq data:

Fig. 4 — Expression of cytochrome P450s in liver cell types. Resident liver cell types and other immune cells are shown in panels (A) and (B), respectively. The cell type with the highest expression of a gene is given the darkest blue and denoted as 100%. The lighter shades of blue show the expression level of the same gene relative to the highest-expressing cell type. A gray color is used when a cell type expresses the same gene at < 1% of the highest-expressing cell type. The numbers on the right represent the ratio of the gene expression change in either periportal (P/C) or centrilobular (C/P) hepatocytes. The numbers on the right are filled in red when statistically significantly enriched and in grey otherwise.

3.4.1. Cyp1 family

Cyp1a1 and Cyp1b1 are not expressed or detected in the sc/sn RNA-seq data at basal levels in liver cell types. Cyp1a2 is the only gene expressed in the Cyp1 family and is predominantly expressed in hepatocytes (Fig. 4A). Cyp1a2 is not expressed in other hepatic cell types and has 3-fold higher expression in centrilobular hepatocytes, compared with periportal hepatocytes.

3.4.2. Cyp2 family

Of the 50 genes in the Cyp2 family (Supplemental Table 1), 23 are expressed in liver cell types (Fig. 4A), 20 of which are highly expressed in hepatocytes. Notable exceptions include Cyp2d22 and Cyp2j6 (highest in cholangiocytes) and Cyp2s1 (myofibroblasts). Within the hepatocyte population, 12 genes are enriched in centrilobular hepatocytes and 8 in periportal hepatocytes. In nonparenchymal cell types, Cyp2 transcripts are distributed across cholangiocytes (17 genes), endothelial cells (7 genes), stellate cells (12 genes), myofibroblasts (11 genes), and Kupffer cells (1 gene).

3.4.3. Cyp3 family

Of the 8 genes in the Cyp3 family (Supplemental Table 1), 4 are expressed in liver cell types and are most highly expressed in hepatocytes (Fig. 4A). Cyp3a11 (the ortholog of CYP3A4, which metabolizes ∼50% of marketed drugs (Zhou, 2008)) is also expressed in all other resident liver cells except Kupffer cells. Besides hepatocytes, Cyp3a13 is expressed in myofibroblasts, and Cyp3a25 is expressed in stellate cells and myofibroblasts. Within hepatocytes, Cyp3a11, Cyp3a25, and Cyp3a59 are enriched in centrilobular hepatocytes.

3.4.4. Cyp4 family

Of the 20 genes in the Cyp4 family (Supplemental Table 1), 9 are expressed in liver cell types (Fig. 4A). Seven out of the 9 Cyp4 genes are most highly expressed in hepatocytes, whereas Cyp4b1 and Cyp4f14 are most highly expressed in endothelial cells and cholangiocytes, respectively. Within the hepatocyte population, 6 Cyp4 genes are enriched in centrilobular hepatocytes and are lowly expressed in periportal hepatocytes.

3.4.5. Bile acid synthetic Cyp enzymes

Cyp7a1, Cyp8b1, Cyp27a1, and Cyp7b1 are major bile acid synthetic Cyp enzymes in the liver (Cali et al, 1991; Cali and Russell, 1991; Pikuleva et al, 2001; Chiang, 2004; Choudhuri and Klaassen, 2022) that are primarily expressed in hepatocytes. Cyp7a1 is also expressed in endothelial cells, stellate cells, and myofibroblasts; Cyp7b1 is also expressed in stellate cells and myofibroblasts; and Cyp27a1 is also expressed in stellate cells, myofibroblasts, and Kupffer cells. Other bile acid synthetic enzymes, including Cyp39a1, which is known for neural cholesterol clearance through bile acid synthesis (Li-Hawkins et al, 2000), as well as Cyp51, which is known for sterol metabolism (Lepesheva and Waterman, 2007; Lorbek et al, 2015), are expressed most highly in cholangiocytes, followed by hepatocytes. Within the hepatocyte population, Cyp7a1, Cyp27a1, and Cyp7b1 are enriched in centrilobular hepatocytes, whereas Cyp39a1 and Cyp51 are enriched in periportal hepatocytes.

3.4.6. Other Cyps

Of the 15 genes in the remaining Cyp family (Supplemental Table 1), 5 are expressed in liver cell types (Fig. 4A). Cyp20a1, which is an orphan cytochrome P450 without known substrates (Durairaj et al, 2020), is expressed highest in stellate cells. Cyp26b1, which metabolizes retinoic acid (Stoney et al, 2016), is expressed highest in endothelial cells.

Besides the resident liver cell types, 8 Cyps are expressed in circulating immune cells that are detected in the liver (Fig. 4B). Notably, among all immune cells, Cyp2e1 is expressed highest in neutrophils, followed by pDCs. Cyp4f13 is expressed in pDCs. Cyp4f16 is expressed highest in MDMs, also by cDCs and pDCs. Cyp4f18 is expressed highest in neutrophils, followed by MDMs, B cells, and cDCs. Cyp4v3 is expressed in MDMs, and Cyp8b1 is expressed in cDCs. Cyp27a1 is expressed highest in cDCs, followed by pDCs and MDMs. Cyp51 is expressed highest in pDCs, followed by cDCs and neutrophils.

3.4.7. Alcohol dehydrogenase

Alcohol dehydrogenase (Adh) metabolizes primary and secondary alcohol groups into aldehydes and ketones (Crabb et al, 2004) and are further metabolized into carboxylic acids by aldehyde dehydrogenases (Aldh) and aldehyde oxidase (Aox) (Huang et al, 1999; Molotkov and Duester, 2003; Oka et al, 2020). Four out of 6 detected Adhs (Supplemental Table 1) are expressed highest in hepatocytes (Fig. 5A). Among various cell types, Adh1 is expressed in all resident liver cell types except Kupffer cells, and Adh5 in all cell types except myofibroblasts. Within the hepatocyte population, Adh1 and Adhfe1, which are mitochondrial Adh (Struys et al, 2005), are enriched in centrilobular hepatocytes.

3.4.8. Aldh1

All 4 detected out of the 7 Aldh1 genes (Supplemental Table 1) are expressed highest in hepatocytes and are also expressed in cholangiocytes (Fig. 5A). Aldh1a1 and Aldh1l1 are also expressed in endothelial cells, stellate cells, and myofibroblasts. Within the hepatocyte population, Aldh1a1 is enriched in centrilobular hepatocytes, while Aldh1b1 and Aldh1l1 are enriched in periportal hepatocytes.

3.4.9. Other Aldhs

Of the 11 remaining Aldhs (Supplemental Table 1), Aldh2 and Aldh3a2 are expressed highest in hepatocytes (Fig. 5A). Aldh2 is expressed in all resident liver cell types, whereas Aldh3a2 is expressed in all liver-resident cell types except myofibroblasts. Aldh3b1 is expressed highest in Kupffer cells. Aldh4a1, Aldh5a1, Aldh6a1, Aldh7a1, Aldh8a1, and Aldh9a1 are expressed highest in hepatocytes. In addition to hepatocytes, Aldh4a1 is expressed in cholangiocytes; Aldh6a1 and Aldh7a1 are expressed in all liver-resident cell types except Kupffer cells; and Aldh9a1 is also expressed in cholangiocytes and endothelial cells. Aldh16a1 is uniquely expressed in Kupffer cells. Among the other Aldhs, Aldh2, Aldh3a2, Aldh6a1, and Aldh9a1 are enriched in centrilobular hepatocytes.

3.4.10. Aox

Of the 2 Aoxs (Supplemental Table 1), Aox1 is expressed in liver cell types (Fig. 5A). The expression of Aox1 is the highest in hepatocytes, followed by myofibroblasts and stellate cells. Aox1 is not enriched in periportal or centrilobular hepatocytes.

3.4.11. Epoxide hydrolases

Epoxide hydrolases (Ephx) add hydroxyl groups to epoxides to improve water solubility and excretion (Decker et al, 2012) and often decrease toxicity. Of the 4 Ephxs (Supplemental Table 1), 2 are expressed in liver cell types (Fig. 5A). Ephx1 is expressed highest in stellate cells and is expressed in all other resident liver cell types except endothelial cells. Ephx2 is expressed highest in hepatocytes and is also expressed in all liver-resident cell types except Kupffer cells. Within the hepatocyte population, Ephx2 is enriched in centrilobular hepatocytes.

3.4.12. Flavin-containing monooxygenases

Flavin-containing monooxygenases (Fmo) perform oxidation reactions on nitrogen- and sulfur-containing compounds, including xenobiotics (Veeravalli et al, 2020). Of the 7 Fmos (Supplemental Table 1), 4 are expressed in liver-cell types (Fig. 5A). Fmo1 is expressed highest in hepatocytes and is also expressed in endothelial cells, stellate cells, and myofibroblasts. Fmo2 is expressed highest in myofibroblasts, followed by cholangiocytes. Fmo3 is only expressed in hepatocytes. Fmo4 is not expressed in liver cell types. Fmo5 is expressed most highly in hepatocytes and is also expressed in all liver-resident cell types except Kupffer cells. Within the hepatocyte population, Fmo1 and Fmo5 are enriched in centrilobular hepatocytes, whereas Fmo3 is enriched in periportal hepatocytes.

3.4.13. Quinone oxidoreductase

Quinone oxidoreductase, NAD(P)H: quinone oxidoreductase 1 (Nqo1) is not expressed or was not detected at basal levels in the sc/sn RNA-seq data. N-ribosyldihydronicotinamide: quinone oxidoreductase 2 (Nqo2) uses N-alkyl nicotinamide derivatives for the metabolism of flavonoids, including melatonin, chloroquine, and resveratrol (Janda et al, 2020). Nqo2 is expressed highest in endothelial cells, followed by hepatocytes and cholangiocytes. Within the hepatocyte population, Nqo2 is enriched in centrilobular hepatocytes.

In immune cells (Fig. 5B), Adh5, out of the 4 Adhs in liver resident cells, is expressed most highly in pDCs and is also expressed in all immune cells except neutrophils. Six out of 14 Aldhs in liver resident cells are expressed in immune cells; Aldh1b1 is expressed in pDC. Among immune cells, Aldh2 is expressed most highly in MDMs, followed by neutrophils, B cells, pDCs, cDCs, and T cells. Aldh3a2 is expressed most highly in pDCs, followed by NK cells in immune cells. Aldh3b1 has the highest expression in pDCs and is also expressed in neutrophils, MDMs, and cDCs in immune cells. The expression of Aldh9a1 and Aldh16a1 is highest in cDCs in immune cells. Aldh9a1 is also expressed in pDCs and MDMs in immune cells. Ephx1, out of the 3 Ephxs in liver resident cell types, is expressed the highest in B cells, followed by CD8 T cells in immune cells. Fmo5, out of the 4 Fmos in liver resident cell types, is expressed in pDCs.

3.4.14. Aldo-keto reductases (Akr)

Aldo-keto reductases (Akr) preferentially utilize NADPH to metabolize various aldehydes and ketones (Barski et al, 2008). Of the 16 Akrs (Supplemental Table 1), 13 are expressed in liver cell types (Fig. 6A).

Fig. 6 — Expression of aldo-keto reductase (Akr), carbonyl reductase (Cbr), carboxylesterase (Ces), and paraoxonase (Pon) in liver cell types. Resident liver cell types and other immune cells are shown in panels (A) and (B), respectively. The cell type with the highest expression of a gene is given the darkest blue and denoted as 100%. The lighter shades of blue show the expression level of the same gene relative to the highest expressing cell type. A gray color is used when a cell type expresses the same gene at < 1% of the highest-expressing cell type. The numbers on the right represent the ratio of the gene expression change in either periportal (P/C) or centrilobular (C/P) hepatocytes. The numbers on the right are filled in red when statistically significantly enriched and filled in grey otherwise.

Akr1a1, Akr1b3, and Akr1b10 are expressed most highly in Kupffer cells, and Akr1b8 was expressed most highly in endothelial cells. In addition to Kupffer cells, Akr1a1 is expressed in all liver-resident cell types; Akr1b3 is expressed in endothelial cells and stellate cells; and Akr1b10 is expressed in endothelial cells.

The 6 genes in the Akr1c family are most highly expressed in hepatocytes except Akr1c19, which is expressed most highly in cholangiocytes, followed by hepatocytes and myofibroblasts. In addition to hepatocytes, Akr1c6 is expressed in all resident liver cell types except Kupffer cells; Akr1c13 is also expressed in Kupffer cells; Akr1c14 and Akr1c20 are also expressed in cholangiocytes and endothelial cells. Akr1c6, Akr1c14, and Akr1c20 are enriched in centrilobular hepatocytes.

Akr1d1 is expressed most highly in hepatocytes, followed by stellate cells and myofibroblasts. Akr1e1 is expressed most highly in cholangiocytes, followed by hepatocytes. Akr7a5 is most highly expressed in hepatocytes, followed by cholangiocytes and endothelial cells. Akr1d1 is enriched in centrilobular hepatocytes, and Akr7a5 is enriched in periportal hepatocytes.

3.4.14. Carbonyl reductases

Carbonyl reductases (Cbr) are NADPH-dependent reductases that metabolize compounds with carbonyl groups, such as prostaglandins and doxorubicin (Forrest and Gonzalez, 2000; Olson et al, 2003; Miura et al, 2008). Three of the 4 Cbrs (Supplemental Table 1) are expressed in liver cell types and are expressed highest in cholangiocytes (Fig. 6A). Cbr1 is also expressed in all liver-resident cell types but myofibroblast; Cbr3 is also expressed in stellate cells; and Cbr4 has equal expression in hepatocytes as cholangiocytes. Cbr1 is enriched in periportal hepatocytes.

3.4.15. Carboxylesterases

Carboxylesterases (Ces) are involved in hydrolysis reactions of esters, amides, thioesters, and carbamates (Laizure et al, 2013). Of the 18 Ces genes (Supplemental Table 1), 11 are expressed in liver cell types (Fig. 6A).

Genes in the Ces1 family are most highly expressed in hepatocytes except Ces1d, which is expressed most highly in cholangiocytes and is also expressed in all liver-resident cell types except Kupffer cells. In addition to hepatocytes, Ces1c is expressed in all resident liver cell types except Kupffer cells. Ces1f is expressed in cholangiocytes, stellate cells, and myofibroblasts, and Ces1g is expressed in cholangiocytes. All genes in the Ces1 family were enriched in centrilobular hepatocytes except Ces1c, which was enriched in periportal hepatocytes.

The expression of Ces2a is the highest in hepatocytes. Ces2e has the highest expression in endothelial cells, followed by hepatocytes. Ces2g has the highest expression in endothelial cells, followed by cholangiocytes. Ces3a and Ces3b have the highest expression in hepatocytes. In addition to hepatocytes, Ces3a is expressed in all resident liver cell types except Kupffer cells, and Ces3b is expressed in stellate cells and myofibroblasts. Ces2a and Ces3a are enriched in centrilobular hepatocytes.

3.4.16. Paraoxonases

Paraoxonases (Pon) hydrolyze compounds with carboxylic acid esters, including organophosphate insecticides (Furlong et al, 2016). All 3 Pons are expressed in liver cell types (Fig. 6A and Supplemental Table 1). Pon1 and Pon3 are expressed most highly in hepatocytes, while Pon2 has the highest expression in endothelial cells. In addition to the cell type with the highest expression, Pon1 is also expressed in all liver-resident cell types except Kupffer cells. Pon2 is expressed in all resident liver cell types, and Pon3 is also expressed in endothelial cells. Pon1 and Pon3 are enriched in centrilobular hepatocytes.

In immune cells (Fig. 6B), 4 Akrs are expressed out of the 13 in liver resident cells. Akr1a1 is expressed the highest in MDMs and is also expressed in all immune cell types. Akr1b3 is expressed the highest in CD8 T cells and is also expressed in all immune cell types except neutrophils in immune cells. Akr1b10 is expressed the highest in NK cells, followed by cDCs and MDM equally in immune cells. Akr7a5 is expressed the highest in cDC, followed by pDCs in immune cells. Cbr1, out of the 3 Cbrs in liver resident cell types, is expressed the highest in CD8 T cells and is also expressed in pDCs and T cells in immune cells. 2 Pons out of the 3 in liver resident cells are expressed in immune cells. Pon2 is expressed the highest in MDMs and is also expressed in all immune cell types except neutrophils. Pon3 is expressed in pDCs.

3.5. Phase-II conjugation enzymes

3.5.1. UDP-glucuronosyltransferases

UDP-glucuronosyltransferases (Ugts) attach a nucleotide sugar glycosyl group to the target molecules (King et al, 2000). Of 21 Ugts (Supplemental Table 2), 8 are expressed in liver cell types (Fig. 7A). The 6 genes in the Ugt2 family are expressed highest in hepatocytes. In addition, Ugt2b1 is expressed in stellate cells; Ugt2b5 is expressed in all liver-resident cells except Kupffer cells; Ugt2b34 is expressed in cholangiocytes and stellate cells; and Ugt2b36 is expressed in all liver-resident cell types except Kupffer cells. Ugt2b1, Ugt2b34, Ugt2b35, and Ugt2b36 are enriched in centrilobular hepatocytes.

The expression of Ugt3a1 and Ugt3a2 is highest in hepatocytes. The expression of Ugt8a is highest in cholangiocytes. Ugt3a1 and Ugt3a2 are enriched in centrilobular hepatocytes.

No Ugts are expressed in resident and circulating immune cells in the liver (Fig. 7B).

3.5.2. Glutathione S-transferases

Glutathione S-transferases (Gsts) conjugate glutathione to electrophilic compounds (Townsend and Tew, 2003). Of 22 the Gsts (Supplemental Table 2), 16 are expressed in liver cell types (Fig. 7A). The expression of 3 out of 4 genes in the Gsta family is highest in hepatocytes. Gsta3 is also expressed in all resident liver cell types, and Gsta4 is also expressed in cholangiocytes and stellate cells. Gsta3 is enriched in centrilobular hepatocytes and Gsta4 is enriched in periportal hepatocytes.

Gstk1 is expressed the highest in endothelial cells, followed by hepatocytes and cholangiocytes with equal expression. Gstk1 is enriched in periportal hepatocytes.

Of the 7 genes in the Gstm family, 2 are expressed most highly in hepatocytes, 3 are expressed most highly in cholangiocytes, and 1 is expressed most highly in endothelial cells. In addition to the cell type with the highest expression, Gstm1 is expressed in all liver-resident cell types; Gstm2 is expressed in stellate cells and myofibroblasts; Gstm5 is expressed in stellate cells; Gstm6 is expressed in cholangiocytes; and Gstm7 is expressed in hepatocytes. Gstm1 and Gstm6 are enriched in centrilobular hepatocytes whereas Gstm7 is enriched in periportal hepatocytes.

Gsto1 and Gstp1 have the highest expression in hepatocytes. Gsto1 is also expressed in endothelial cells and Kupffer cells. Gstp1 is also expressed in all liver-resident cell types except myofibroblasts. Gsto1 and Gstp1 are enriched in periportal hepatocytes.

The expression of Gstt1 is highest in cholangiocytes, and the expression of Gstt2 and Gstt3 is equally the highest in hepatocytes and cholangiocytes. Gstt1 is also expressed in hepatocytes, stellate cells, and myofibroblasts. Gstt2 is also expressed in endothelial cells and stellate cells. Gstt2 is enriched in centrilobular hepatocytes, whereas Gstt3 is enriched in periportal hepatocytes.

Gstz1 is expressed the highest in hepatocytes and is also expressed in all resident liver cell types but Kupffer cells.

In immune cells (Fig. 7B), 5 Gsts are expressed out of 16 in liver resident cells. Gsta3 is expressed in neutrophils. Gstm1 is expressed the highest in MDMs, followed by neutrophils in immune cells. Gsto1 is expressed in MDMs and is also expressed in cDCs in immune cells. Gstp1, among immune cells, is expressed most highly in MDMs, followed by T cells, pDCs, CD8 T cells, cDCs, and NK cells. Gstt2 is expressed in CD8 T cells.

3.5.3. Sulfotransferases

Sulfotransferases (Sult) catalyze sulfate conjugation reactions to multiple compounds, including hormones, xenobiotics, and neurotransmitters (Negishi et al, 2001). Of the 18 Sults (Supplemental Table 2), 5 are expressed in liver cell types (Fig. 7A). Sult1a1, Sult1b1, and Sult1d1 are expressed the highest in hepatocytes (Fig. 7A). Sult1a1 is expressed in all liver-resident cell types. Sult2b1 and Sult5a1 are expressed the highest in cholangiocytes and hepatocytes, respectively. Sult1a1 and Sult5a1 are enriched in periportal hepatocytes.

Sult1a1, out of 5 Sults in liver resident cells, is expressed in cDCs (Fig. 7B).

3.5.4. N-acetyltransferases

N-acetyltransferases (Nats) catalyze acetylation reactions (Sim et al, 2008). Of the 8 Nats (Supplemental Table 2), 3 are expressed in liver cell types (Fig. 7A). Nat9, Nat10, and Nat14 are expressed most highly in cholangiocytes. Nat9 is also expressed in hepatocytes and endothelial cells. Nat10 and Nat14 are also expressed most highly in hepatocytes. Nat10 is enriched in centrilobular hepatocytes.

In immune cells (Fig. 7B), 2 of the 3 Nats are expressed compared with liver resident cells. Nat9 and Nat10 are expressed in pDCs and CD8 T cells, respectively.

3.5.5. Hepatic methyltransferases

Hepatic methyltransferases (mts) attach methyl groups to substrates. Arsenic (3) methyltransferase (As3mt) is involved in a series of metabolic steps that involve the methylation of inorganic arsenic (Mersaoui et al, 2022). Catechol-O-methyltransferase (Comt) catalyzes methylation reactions of catecholamines, as well as other substrates including estrogen and polyphenols (Bastos et al, 2017). Thiopurine methyltransferase (Tpmt) catalyzes the methylation of thiopurine drugs by using S-adenosyl-L-methionine as the methyl donor (Peng et al, 2008). All 3 methyltransferases are expressed in liver cell types (Fig. 7A and Supplemental Table 2). As3mt has the highest expression in cholangiocytes. Comt and Tpmt are expressed highest in hepatocytes. As3mt is also expressed in hepatocytes, endothelial cells, and stellate cells. Comt is expressed in all liver-resident cell types, and Tpmt is also expressed in cholangiocytes. As3mt is enriched in periportal hepatocytes.

Among 3 the methyltransferases that are expressed in liver resident cell types, 2 are expressed in immune cells (Fig. 7B). As3mt is expressed the highest in pDCs, followed by NK cells in immune cells. Comt is expressed the highest in MDMs in immune cells and is also expressed in pDCs, T cells, neutrophils, cDCs, and NK cells.

3.5.6. Amino acid conjugation enzymes

Amino acid conjugation enzymes (ats), including glycine N-acetyltransferase (Glyat), transfer an acyl group to glycine and glutamine and are involved in the detoxification of compounds, including salicylic acid and isovaleric acid (Mawal and Qureshi, 1994; Matsuo et al, 2012). Bile acid-CoA: amino acid N-acyltransferase (Baat) conjugates taurine and glycine to bile acids (Falany et al, 1994; O’Byrne et al, 2003). Bile acid-CoA synthetase (Slc27a5 [Bile Acid-CoA Ligase, Bal]) catalyzes the formation of fatty acid acyl-CoA, including bile acid-CoA thioesters (Steinberg et al, 1999, 2000; Mihalik et al, 2002). The expression of Glyat, Baat, and Slc27a5 (Bal) is highest in hepatocytes (Fig. 7A). Glyat is also expressed in cholangiocytes and myofibroblasts. Slc27a5 (Bal) is also expressed in endothelial cells and stellate cells. Slc27a5 (Bal) is enriched in centrilobular hepatocytes.

No amino acid conjugation enzymes are expressed in resident and circulating immune cells in the liver (Fig. 7B).

3.5.7. Cofactor synthetases in hepatic phase-II metabolism

Cofactor synthetases in hepatic phase-II metabolism: UDP-glucuronic acid is synthesized by UDP-glucose pyrophosphorylase (Ugp) using glucose-1-phosphate and UTP (Thoden and Holden, 2007). UDP-glucose 6-dehydrogenase (Ugdh) converts UDP-glucose to UDP-glucuronate (Price et al, 2023). The expression of Ugp2 and Ugdh is the highest in hepatocytes (Fig. 7A). Udp2 is also expressed in all resident liver cell types, and Ugdh is also expressed in cholangiocytes and endothelial cells.

Glutathione is the cofactor for GSTs, and the glutamate-cysteine ligase catalytic subunit (Gclc) and glutamate-cysteine ligase modifier subunit (Gclm) are the rate-limiting enzymes involved in the synthesis of glutathione (Misra and Griffith, 1998). Glutathione synthetase (Gss) catalyzes the production of glutathione from gamma-glutamylcysteine and glycine (Gali and Board, 1995; Dahl et al, 1997). The expression of Gclc and Gclm is highest in hepatocytes. Gss is expressed highest in hepatocytes and endothelial cells equally. Gclc and Gclm are also expressed in all liver-resident cell types. Gclm and Gss are enriched in periportal hepatocytes.

The cofactor for sulfonation, 3`-phosphoadenosine-5`-phosphosulfate (PAPS), is synthesized by PAPS synthetases (Papss). Papss1 and Papss2 are expressed highest in cholangiocytes and stellate cells. Papss1 is also expressed in endothelial cells, stellate cells, and myofibroblasts. Papss2 is also expressed in hepatocytes and myofibroblasts. Papss2 is enriched in centrilobular hepatocytes.

Both glutathione synthesis enzymes, Gclc and Glcm, are expressed in immune cells (Fig. 7B). Gclc is expressed highest in T cells and is also expressed in CD8 T cells, pDCs, B cells, and NK cells. Gclm is expressed in pDCs. Papss1, out of the 2 Papss’ in liver resident cells, is expressed the highest in pDCs, followed by MDMs and cDCs in immune cells. Ugdh is expressed in NK cells and pDC in immune cells. Ugp2 is expressed the highest in neutrophils and is also expressed in NK cells, pDCs, cDCs, T cells, and B cells in immune cells.

3.6. Transporters

Transporters regulate the disposition of substrates in the liver and include multiple members in the ATP-binding cassette (Abc), ATPase (Atp), solute carrier (Slc), and organic solute carrier (Slco) families.

3.6.1. Slco/Oatp transporters

Slco/Oatp transporters, commonly named organic anion transporting polypeptides (Oatp), are involved in the uptake of substrates, including statins and chemotherapeutics (Schulte and Ho, 2019). The expression of Slco1a1 (Oatp1a1), Slco1a4 (Oatp1a4), and Slco1b2 (Oatp1b2) is highest in hepatocytes (Fig. 8A). The expression of Slco3a1 (Oatp3a1) is highest in stellate cells. Slco1a1 (Oatp1a1) is also expressed in stellate cells and myofibroblasts; Slco1b2 (Oatp1b2) is also expressed in all resident liver cell types except Kupffer cells; and Slco3a1 (Oatp3a1) is also expressed in cholangiocytes, endothelial cells, and myofibroblasts. Slco1a1 (Oatp1a1), Slco1a4 (Oatp1a4), and Slco1b2 (Oatp1b2) are enriched in centrilobular hepatocytes.

Fig. 8 — Expression of drug transporters in resident liver cell types. Resident liver cell types and other immune cells are shown in panels (A) and (B), respectively. The cell type with the highest expression of a gene is given the darkest blue and denoted as 100%. The lighter shades of blue show the expression level of the same gene relative to the highest-expressing cell type. A gray color is used when a cell type expresses the same gene at < 1% of the highest-expressing cell type. The numbers on the right represent the ratio of the gene expression change in either periportal (P/C) or centrilobular (C/P) hepatocytes. The numbers on the right are filled in red when statistically significantly enriched and in grey otherwise.

Among the 4 Slco (Oatp) family members, Slco3a1 (Oatp3a1) is expressed in immune cells, and the expression was the highest in CD8 T cells, followed by T cells, cDCs, and pDCs (Fig. 8B).

3.6.2. Organic anion transporters

Organic anion transporters (Oats) are involved in the uptake of common drugs (eg, antibiotics, antivirals, diuretics), toxicants, and nutrients (Nigam et al, 2015) and are encoded by Slc22a6-Slc22a8 (Supplemental Table 3). Under basal conditions, Oats are not expressed or expressed high enough in liver cell types in the sc/sn RNA-seq data.

3.6.3. Organic cation transporters

Organic cation transporters (Octs), as shown in Fig. 8A, Slc22a1 (organic cation transporter 1, Oct1) facilitate the entry of nutrients and xenobiotics, such as metformin, into the cell with a broad substrate specificity (Brosseau and Ramotar, 2019; Zeng et al, 2023). Slc22a1 (Oct1) is expressed highest in hepatocytes and is enriched in centrilobular hepatocytes. Slc22a2 (Oct2) and Slc22a3 (Oct3) are not expressed or undetected at basal levels in liver cell types (Supplemental Table 3).

No Octs are expressed in resident and circulating immune cells in the liver (Fig. 8B).

3.6.4. Nucleoside transporters

Nucleoside transporters (nts), concentrative nucleoside transporters (Cnts), and equilibrative nucleoside transporters (Ents) modulate the cellular entry of endogenous and synthetic nucleosides, such as anticancer and antiviral drugs (Gray et al, 2004). Of 3 Cnts and 3 Ents (Supplemental Table 3), Slc28a2 (Cnt2) and Slc29a3 (Ent3) are expressed in liver cell types and are expressed highest in Kupffer cells (Fig. 8A). Slc29a1 (Ent1) is expressed highest in endothelial cells, is also expressed in all liver-resident cell types except myofibroblasts, and is enriched in centrilobular hepatocytes.

In the immune cells, Slc28a2 (Cnt2) is expressed the highest in CD8 T cells, followed by T cells, NK cells, and B cells in immune cells (Fig. 8B). Slc29a1 (Ent1) and Slc29a3 (Ent3) are also expressed in immune cells, and their expressions are highest in pDCs. Slc29a1 (Ent1) is also expressed in MDMs, and Slc29a3 (Ent3) is also expressed in MDMs and cDCs.

3.6.5. Multidrug and toxin extrusion 1

Multidrug and toxin extrusion 1 (Mate1) is encoded by Slc47a1 and is an efflux transporter that pumps out endogenous metabolites and xenobiotics (Yonezawa and Inui, 2011). Sla47a1 (Mate1) is expressed most highly in hepatocytes and is enriched in centrilobular hepatocytes (Fig. 8A). Slc47a2 (Mate2) is not expressed or undetected at basal levels in liver cell types. Slc47a1 (Mate1) is not expressed in resident and circulating immune cells in the liver (Fig. 8B).

3.6.6. Multidrug resistance proteins

Multidrug resistance proteins (Mdr), Abcb1a (multidrug resistance 1a, Mdr1a/P-glycoprotein, Pgp), and Abcb1b (multidrug resistance 1b, Mdr1b/Pgp) export xenobiotics into bile (van Helvoort et al, 1996). Abcb4 (multidrug resistance 2/3, Mdr2/3) is a lipid efflux transporter that flops phosphatidylcholine into bile, and its mutation is linked to progressive familial intrahepatic cholestasis (Rosmorduc et al, 2003). As shown in Fig. 8A, Abcb1a (Mdr1a/Pgp) and Abcb1b (Mdr1b/Pgp) are expressed highest in cholangiocytes and myofibroblasts, respectively. Abcb4 (Mdr2/3) is expressed the highest in hepatocytes. Abcb1a (Mdr1a/Pgp) is also expressed in myofibroblasts, and Abcb4 (Mdr2/3) is also expressed in stellate cells and myofibroblasts. Abcb4 (Mdr2/3) is enriched in centrilobular hepatocytes.

Abcb1a (Mdr1a/Pgp) is expressed the highest in NK cells and T cells in immune cells (Fig. 8B). Abcb1b (Mdr1b/Pgp) is expressed in pDCs.

3.6.7. Multidrug resistance-associated proteins

Multidrug resistance-associated proteins (Mrps) are organic anion transporters that export endo- and xenobiotics, including methotrexate (MTX), glutathione, glucuronide, and sulfate-conjugated neutral drugs, and bilirubin glucuronides (Borst et al, 2000). The expression of Abcc1 (Mrp1) and Abcc3 (Mrp3) is highest in Kupffer cells. Abcc2 (Mrp2) and Abcc6 (Mrp6) are expressed most highly in hepatocytes. Abcc4 (Mrp4) is expressed the highest in endothelial cells. Abcc2 (Mrp2) is also expressed in stellate cells and myofibroblasts. Abcc5 (Mrp5) is not expressed in resident liver cell types. Abcc3 (Mrp3) is also expressed in hepatocytes and cholangiocytes. Abcc2 (Mrp2) and Abcc3 (Mrp3) are enriched in centrilobular hepatocytes.

One out of 5 genes in the Abcc family expressed in resident liver cell types is expressed in immune cells (Fig. 8B). Abcc1 (Mrp1) is expressed the highest in pDCs, followed by cDCs and CD8 cells in immune cells.

3.6.8. Breast cancer resistance protein

Breast cancer resistance protein (Bcrp) is encoded by Abcg2 and limits the intracellular accumulation of xenobiotics by active extrusion (Allen et al, 1999). Abcg2 (Bcrp) is expressed most highly in hepatocytes and stellate cells equally. Abcg2 (Bcrp) is also expressed in all liver-resident cell types except Kupffer cells.

Abcg2 (Bcrp) is not expressed in immune cell types in the liver.

3.6.9. Bile acid transporters

Bile acid transporters, Slc10a1 (sodium taurocholate transporting polypeptide, Ntcp) plays a key role in the enterohepatic circulation of bile, lipophilic compounds, and nutrients by transporting conjugated bile salts into the liver (Hagenbuch and Meier, 1994; Ho et al, 2004). Slc10a2 (apical sodium-dependent bile salt transporter, Asbt) is highly expressed in the small intestine and involved in enterohepatic circulation by importing bile acids (Wong et al, 1995; Craddock et al, 1998). Abcb11 (bile salt export pump, Bsep) is involved in the biliary excretion of bile salts (Hayashi et al, 2005).

Slc10a1 (Ntcp) is expressed most highly in hepatocytes but also expressed in cholangiocytes and stellate cells (Fig. 8A). Slc10a2 (Asbt) is expressed highest in cholangiocytes in the liver. Abcb11 (Bsep) is expressed the highest in hepatocytes but is also expressed in stellate cells and myofibroblasts. Slc10a1 (Ntcp) and Abcb11 (Bsep) are enriched in centrilobular and periportal hepatocytes, respectively.

No bile acid transporters are expressed in hepatic immune cells (Fig. 8B).

3.6.10. Cholesterol and lipid transporters and an anion exchanger

Cholesterol and lipid transporters and an anion exchanger, Abca1 (cholesterol efflux regulatory protein, Cerp), maintain cellular levels of cholesterol and lipids (Schmitz and Langmann, 2001). Abcg5 (Sterolin1) and Abcg8 (Sterolin2) secrete cholesterol into the biliary lumen (Hazard and Patel, 2007). Atp8b1 (familial intrahepatic cholestasis 1, Fic1) flips phosphatidylcholine to the inner hepatic membrane to maintain the lipid asymmetry within cell membranes. The dysfunction of Atp8b1 (Fic1) is involved in progressive familial intrahepatic cholestasis (Cai et al, 2009), along with other causes of familial intrahepatic cholestasis by impairment, namely Abcb11 (Bsep) and Abcb4 (Mdr2/3) leading to Fic2 and Fic3, respectively (Giovannoni et al, 2015). Slc4a2 (anion exchange protein 2, Ae2) is involved in pH regulation by facilitating the exchange of chloride and bicarbonate ions across the cell membrane (Aranda et al, 2004).

As shown in Fig. 8A, the expression of Abca1 (Cerp) is highest in Kupffer cells. Abcg5 (Sterolin1) and Abcg8 (Sterolin2) are expressed most highly in hepatocytes. Atp8b1 (Fic1) is expressed the highest in stellate cells. Slc4a2 (Ae2) is expressed the highest in cholangiocytes. Abca1 (Cerp) is also expressed in all resident liver cell types except endothelial cells. Atp8b1 (Fic1) is expressed in hepatocytes, cholangiocytes, and myofibroblasts, and Slc4a2 (Ae2) is expressed in endothelial cells and Kupffer cells. Abca1 (Cerp), Abcg5 (Sterolin1), Abcg8 (Sterolin2), and Atp8b1 (Fic1) are enriched in centrilobular over periportal hepatocytes.

Among the 4 cholesterol and lipid transporters expressed in resident liver cell types, Abca1 (Cerp) is expressed in B cells. Slc4a2 (Ae2) is expressed in NK cells, pDCs, T cells, and CD8 T cells.

3.6.11. Organic solute and steroid transporters

Organic solute and steroid transporters (Osts) α and Ostβ are efflux transporters of bile acids and steroids across the basolateral membrane (Ballatori et al, 2009). Under basal conditions, Slc51a (Ostα) and Slc51b (Ostβ) are not expressed in liver cell types.

3.7. Transcription factors related to xenobiotic biotransformation

3.7.1. Xenobiotic-sensing transcription factors

Aryl hydrocarbon receptor (Ahr), Nr1i2 (PXR), and Nr1i3 (CAR) are critical regulators of genes involved in xenobiotic biotransformation (Puga et al, 2002; Wada et al, 2009; Dutta et al, 2022; Lv et al, 2022). The expression of Ahr is the highest in endothelial cells (Fig. 9A). The expression of Nr1i2 (PXR) and Nr1i3 (CAR) is the highest in hepatocytes. Ahr is also expressed in hepatocytes and myofibroblasts. Nr1i2 (PXR) is also expressed in cholangiocytes and myofibroblasts. Nr1i3 (CAR) is also expressed in stellate cells and myofibroblasts. Ahr, Nr1i2 (PXR), and Nr1i3 (CAR) are enriched in centrilobular hepatocytes.

Ahr is expressed the highest in cDCs, followed by pDCs, NK cells, and MDMs in immune cells (Fig. 9B). Nr1i2 (PXR) and Nr1i3 (CAR) are not expressed in other immune cells in the liver.

3.7.2. Fatty acid-sensing nuclear receptors

Peroxisome proliferator-activated receptors (PPAR) regulate fatty acid and energy metabolism (Tyagi et al, 2011). Ppara (PPARα) and Pparg (PPARγ) are expressed most highly in hepatocytes (Fig. 9A). Ppard (PPARδ) is expressed the highest in stellate cells. Ppara (PPARα) is also expressed in stellate cells and myofibroblasts. Ppard (PPARδ) is also expressed in all liver-resident cell types except Kupffer cells. Ppara (PPARα), Ppard (PPARδ), and Pparg (PPARγ) are enriched in centrilobular hepatocytes.

Of the 3 Ppars expressed in resident liver cell types, only Ppard (PPARδ) is expressed in pDCs (Fig. 9B).

3.7.3. Nuclear factor erythroid 2-related factor 2

Nuclear factor erythroid 2-related factor 2 (Nfe2l2, Nrf2) regulates genes involved in oxidative stress response and cytoprotection, such as phase-II detoxifying enzymes, to neutralize reactive electrophiles (Huang et al, 2000). The expression of Nfe2l2 (Nrf2) is the highest in endothelial cells, is also expressed in all resident liver cell types, and is enriched in centrilobular hepatocytes (Fig. 9A).

Nfe2l2 (Nrf2) is expressed the highest in neutrophils in immune cells and is also expressed in all immune cell types (Fig. 9B).

3.7.4. Bile acid-regulating nuclear receptors

Bile acid-regulating nuclear receptors, such as nuclear receptor 1h4 and Nr1h4 (farnesoid X receptor, FXR), play a key role in the regulation of bile acid synthesis and conjugation, as well as lipid and glucose homeostasis, as well as the immune response (Makishima et al, 1999; Modica et al, 2010). Nuclear receptor 0b2, Nr0b2 (small heterodimer partner, SHP), is an orphan nuclear receptor that regulates the expression of genes involved in the metabolism and disposition of bile acids and lipids, and gluconeogenesis (Zhang et al, 2011). Nuclear receptor 5a2, Nr5a2 (liver receptor homolog-1, LRH1) regulates the synthesis of bile acids and triglycerides, as well as cholesterol homeostasis (Wang et al, 2005).

Nr1h4 (FXR) is expressed the highest in stellate cells (Fig. 9A); Nr0b2 (SHP) is expressed the highest in cholangiocytes, and Nr5a2 (LRH1) is expressed the highest in myofibroblasts. In addition to the highest-expressing cell type, Nr1h4 (FXR) is expressed in hepatocytes, cholangiocytes, and myofibroblasts; Nr0b2 (SHP) is expressed in hepatocytes; and Nr5a2 (LRH1) is expressed in all liver-resident cell types except Kupffer cells. Nr1h4 (FXR) and Nr5a2 (LRH1) are enriched in centrilobular hepatocytes, and Nr0b2 (SHP) is enriched in periportal hepatocytes.

No bile acid-regulating nuclear receptors are expressed in hepatic immune cells (Fig. 9B).

3.7.5. Hepatocyte nuclear factor 4a

Hepatocyte nuclear factor 4a (Hnf4a and Hnf4α) plays a key role in liver development and modulates the expression of genes involved in xenobiotic biotransformation (Hwang-Verslues and Sladek, 2010). Hnf4a (Hnf4α) is expressed the highest in hepatocytes (Fig. 9A). Hnf4a (Hnf4α) is also expressed in cholangiocytes, stellate cells, and myofibroblasts.

Hnf4a (Hnf4α) is not expressed in immune cells (Fig. 9B).

3.7.6. Liver X receptors β and α

Liver X receptors β and α (LXRβ and LXRα), encoded by Nr1h2 and Nr1h3, respectively, are involved in the regulation of xenobiotic and lipid metabolism, as well as inflammation (Jakobsson et al, 2012; Schulman, 2017). Nr1h2 (LXRβ) and Nr1h3 (LXRα) are expressed the highest in endothelial cells and Kupffer cells, respectively. Nr1h2 (LXRβ) is also expressed in cholangiocytes, stellate cells, and Kupffer cells. Nr1h3 (LXRα) is also expressed in hepatocytes.

In immune cells (Fig. 9B), both Nr1h2 (LXRβ) and Nr1h3 (LXRα) are expressed. The expression of Nr1h2 (LXRβ) is the highest in pDCs among immune cells and is also expressed in all immune cell types except neutrophils. Nr1h3 (LXRα) is expressed in MDMs.

3.7.7. Retinoic acid and related receptors

Retinoic acid receptors (Rars) are nuclear receptors that are activated by all-trans retinoic acid and 9-cis retinoic acid that regulate cell growth, differentiation, and survival (le Maire et al, 2012). RAR-related orphan receptors (Rors) regulate the circadian expression of genes, as well as phase-I and -II biotransformation enzymes (Wang et al, 2010). Retinoid X receptors (Rxrs), in addition to activation by retinoic acid, heterodimerize with various nuclear receptors, such as FXR, PXR, CAR, and PPARs (Evans and Mangelsdorf, 2014). Rara (RARα) and Rarb (RARβ) are expressed most highly in stellate cells (Fig. 9A). Rarg (RARγ) is expressed the highest in endothelial cells. Rora (RORα) is expressed the highest in myofibroblasts. The expression of Rorc (RORγ) is the highest in hepatocytes. Rxra (RXRα) and Rxrb (RXRβ) are expressed the highest in Kupffer cells and endothelial cells, respectively.

In addition to the highest-expressing cell type, Rara (RARα) is expressed in cholangiocytes, endothelial cells, and Kupffer cells; Rarb (RARβ) is expressed in endothelial cells and myofibroblasts; Rarg (RARγ) is expressed in stellate cells; Rora (RORα) is expressed in all liver-resident cell types except Kupffer cells; Rorc (RORγ) is expressed in cholangiocytes and myofibroblasts; Rxra (RXRα) is expressed in all liver-resident cell types except cholangiocytes; and Rxrb (RXRβ) is expressed in cholangiocytes and Kupffer cells. Rora (RORα) and Rxra (RXRα) are enriched in centrilobular hepatocytes.

Of the 3 Rars expressed in the liver, 2 are expressed in immune cell types (Fig. 9B). Rara (RARα) is expressed the highest in neutrophils and is also expressed in all immune cell types. Rarb (RARβ) is expressed in MDMs. Of the 2 Rors in liver resident cell types, Rora (RORα) is expressed the highest in T cells, followed by NK cells in immune cells. Of the 2 Rxrs in liver-resident cell types, Rxrb (RXRβ) is expressed the highest in pDCs in immune cells and is also expressed in all immune cell types except neutrophils.

4. Discussion

In summary, the present study systematically characterized the cell-type-specific and zonal distribution of DPGs in the liver using single-cell transcriptomics and cross-referenced with spatial transcriptomics. The 195 DPGs profiled (Supplemental Table 1–4) are most highly expressed in hepatocytes (61.3%), followed by cholangiocytes (11.2%), endothelial cells (7.2%), Kupffer cells (5.3%), stellate cells (5.1%), myofibroblasts (2.9%), hepatic pDCs (3.6%), MDMs (0.7%), CD8 T cells (0.6%), and neutrophils (0.2%) (Fig. 4, Fig. 5, Fig. 6, Fig. 7, Fig. 8, Fig. 9). In addition, the present study shows that 47.7% and 12.3% of DPGs are enriched in centrilobular and periportal hepatocytes, respectively, while the remaining 40% of DPGs are not significantly enriched in either lobule. The present study is in line with previous results that hepatocytes, especially those in the centrilobular region, highly express enzymes involved in xenobiotic biotransformation (Sahi et al, 2010; Ahn et al, 2019; Cunningham and Porat-Shliom, 2021). The present results also show that certain DPGs are distributed and uniquely enriched and/or significantly expressed in resident nonparenchymal cells and circulating immune cells that reside in the liver. The DPGs that are expressed in nonparenchymal cells and immune cells may serve as additional repertoires for xenobiotic biotransformation and other metabolic functions in the liver. A systematic profiling of well-characterized DPGs expressed in the liver across hepatic lobules and cell types using sc/sn RNA-seq improves the detection of these genes with greater precision and resolution and is important for further advancing the knowledge of mechanistic insights into hepatotoxicity and chemical-induced liver diseases.

The present study has demonstrated that in addition to hepatocytes, which are the major cell type for xenobiotic biotransformation, many DPGs are expressed in nonparenchymal cells in the liver (albeit usually at lower levels than hepatocytes), corroborating previous findings that nonparenchymal cells also express DPGs. For example, similar to the present study showing mouse cholangiocytes express various genes in the Cyp2 family, Cyp3a11, Ephx2, as well as Gsts, western blotting, and immunohistochemistry showed that isolated human cholangiocytes have been shown to express those in the CYP1, CYP2, and CYP3 families, as well as EPHXs and GSTs (Lakehal et al, 1999). In isolated hepatic rat endothelial cells and Kupffer cells, certain drug-metabolizing enzymes, such as Cyps, Ephxs, and Gsts, were detected at lower levels than in hepatocytes (Steinberg et al, 1987; Sørensen et al, 2015) and were upregulated by phenobarbital, 3-methylcholanthrene, and Alachlor 1254 (Steinberg et al, 1987). The presence of various DPGs in endothelial cells suggests their involvement in the liver-specific metabolism of xenobiotics. For example, Cyp2e1 and Adh1 are expressed in mouse hepatic endothelial cells (Figs. 4 and 5), and rat hepatic endothelial cells express the enzymes CYP2E1 and ADH1, which were shown to metabolize xenobiotics, such as benzo(a)pyrene, aflatoxin B1, and ethanol (Steinberg et al, 1990; Yang et al, 2021).

Similarly, previous work reported that other nonparenchymal cells express DPGs. Isolated human hepatic stellate cells expressed ADH and ALDH enzymes, and their expression is induced by ethanol and acetaldehyde exposures, indicating their capacity to perform alcohol and aldehyde oxidation reactions (Casini et al, 1998). Previous research using primary cells from humans and rats revealed that stellate cells express several genes in the CYP1–4 families, although at low abundance compared with hepatocytes, determined using northern blot and gene chip analysis (Piscaglia et al, 1999; Marek et al, 2007). This suggests that hepatic stellate cells have drug-metabolizing capabilities. In the present study, mouse hepatic stellate cells expressed DPGs, including Adh1, and several Aldhs, as well as genes in the Cyp2–4 families (Figs. 4 and 5). In contrast to human primary stellate cells, Cyp1a2 was not expressed or expressed at high enough levels during basal conditions (Fig. 4), which may be due to human-to-mouse species differences. In rats, isolated myofibroblasts have been shown to express AHR and CYP1A enzyme activity, as determined using aryl hydrocarbon hydroxylase (AHH), 7-ethoxy-resorufin O-deethylation (EROD), and 7-methoxyresorufin O-demethylation (MROD) assays (Peterson and Rowden, 1998). In the present sc/sn RNA-seq data, Cyp1a2 is not expressed or expressed highly in mouse myofibroblasts; however, as Ahr is expressed (Fig. 9), its activation may be able to induce Cyp1a2 at higher levels under toxicological insults or pharmacological conditions (Vrzal et al, 2009). In rodent models, Kupffer cell depletion by gadolinium chloride resulted in a reduction of CYP1A1, CYP1A2, CYP2B1, and CYP2E1 content and activities, which are mostly attributable to hepatocytes (Fig. 4) (Ding et al, 2004; Kim et al, 2011; Park et al, 2015). Collectively, we found that many DPGs are expressed in non-parenchymal cells, albeit at lower levels than hepatocytes of mouse liver. The presence of these DPGs in nonparenchymal cells provides additional information for xenobiotic biotransformation and/or supports other hepatic metabolic functions.

The present study demonstrated that certain DPGs are most highly enriched in nonparenchymal cells (Fig. 4, Fig. 5, Fig. 6, Fig. 7, Fig. 8, Fig. 9). Our findings are consistent with previous research indicating that specific DPGs are highly expressed in nonparenchymal cells. For example, AKR1B10 (the human ortholog of Akr1b8) is highly expressed in cholangiocytes (Zhao et al, 2024). The ABCC3 (MRP3) protein is found in the basolateral membrane of rat cholangiocytes as determined by immunohistochemistry and western blot (Soroka et al, 2001). The activation of LXRβ upregulates Abca1 and increases cholesterol export in cultured rat cholangiocytes (Xia et al, 2012). Induction of PPARγ using an adenoviral vector in rat stellate cells reversed markers of stellate cell activation, such as collagen and smooth muscle actin, to a quiescent state in vitro (Hazra et al, 2004). Nr1h4 (FXR) and Rarb were highly expressed in sorted mouse liver cells (Zummo et al, 2023). CYP20A1 expression, as quantified using gene chip analysis, is observed in cultured human hepatic stellate cells (Marek et al, 2007). Similar to the present study, high expression of FMO2 is noted in human fibrotic livers (Dai et al, 2024). ALDH3B1 and ALDH16A1 are highly expressed in Kupffer cells, as reported using the Human Protein Atlas (Karlsson et al, 2021). LXRα and RXRa were expressed highly in Kupffer cells using sorted mouse livers (Zummo et al, 2023). Our study has provided new insights into the relative distribution of these DPGs compared with hepatocytes and other nonparenchymal cells. The abundance of these DPGs in nonparenchymal cells may significantly contribute to the metabolism of xenobiotics and intermediary metabolites.

It has been suggested that nonparenchymal cells may interact with hepatocytes to regulate the expression of DPGs. For example, coculturing HepG2 cells and endothelial cells has been shown to increase the expression of CYPs over time, suggesting that endothelial cells may secrete distinct paracrine signals to support the expression of these enzymes in hepatocytes. (Ohno et al, 2008). The presence of Kupffer cells is essential for maintaining CYP enzyme levels and may play a significant role in conditions such as sepsis and ischemia-reperfusion injury in rodent models (Kim et al, 2011; Park et al, 2015). In rats, depletion of Kupffer cells leads to increased activities of GST enzymes, indicating possible regulatory or compensatory mechanisms affecting other liver cell types (Steinberg et al, 1987; Ding et al, 2004). Inflammatory activities by Kupffer cells during conditions such as alcoholic fatty liver disease and sepsis contribute to alterations in hepatic drug-metabolizing enzymes in rodents (Kim et al, 2011; Park et al, 2015). Proinflammatory mediators released by Kupffer cells, including tumor necrosis factor-α and nitric oxide, can downregulate CYP2B1 (Milosevic et al, 1999). Additionally, the activity of DPGs in 1 liver cell type can impact another cell type. For example, reactive oxygen species derived from CYP2E1 in hepatocytes can activate hepatic stellate cells, leading to increased α-smooth muscle actin expression, collagen production, and cell proliferation in a coculture system of rat hepatocytes and hepatic stellate cells (Nieto et al, 2002). Future studies using transcription factor network modeling and computational predictions of cell-cell communication may provide further insights into the mechanisms underlying the coexpression patterns of DPGs and other genes among various liver cell types.

As shown in the present study (Fig. 4, Fig. 5, Fig. 6, Fig. 7, Fig. 8, Fig. 9), circulating immune cells that reside in the liver express several DPGs, including members of the Cyp4 family, Aldhs, Akrs, phase-II enzymes, uptake and efflux transporters, and transcription factors related to xenobiotic biotransformation. For example, Cyp4f16 and Cyp4f18 are most highly expressed in MDMs and neutrophils (Fig. 4); Aldh3b1 in pDC (Fig. 5); Gsto1 in MDMs (Fig. 6); Ent3 in pDC (Fig. 7); and Nrf2 in neutrophils (Fig. 8). Immune cells, including T cells, macrophages, and DCs, utilize these phase-I enzymes for fatty acid oxidation, energy metabolism, and to support immunological functions (Singh et al, 2017; Jarrar and Lee, 2019; Wu et al, 2023). For example, ADH and ALDH are involved in maintaining T cell functions (Bazewicz et al, 2019), while Akrs play a role in eicosanoid metabolism in immune cells for inflammatory processes (Theken et al, 2011). Furthermore, macrophages utilize cholesterol metabolism pathways in response to activation signals to support host defense processes (Lee and Bensinger, 2022). Enzymes like CYP8B1 and CYP27A1 are expressed in macrophages and DCs and may participate in bile acid metabolism pathways for sterol elimination (Quinn et al, 2005). Cholesterol also influences the polarization of Kupffer cells and macrophages toward M1 macrophage-like phenotypes (Patankar et al, 2018). AKRs help detoxify reactive metabolites from oxidative stress in macrophages and DCs and play a role in the metabolism of prostaglandins and leukotrienes, which are critical immunological modulators (Zhao et al, 2024). GSTs, together with NRF2, protect immune cells, such as neutrophils and macrophages, from reactive oxygen species (Menon et al, 2014, 2015; van de Wetering et al, 2021). The enzymes encoded by DPGs that are expressed in immune cells may directly impact disease. For example, ALDH2 expression in DCs is critical in graft-versus-host disease (Thangavelu et al, 2019), and ALDH-positive macrophages and DCs are reduced in patients with ulcerative colitis (Magnusson et al, 2016). ENT3 is involved in antigen presentation and lysosomal functions in DCs (Hsu et al, 2012; Hsieh et al, 2023). Although the expression levels of DPGs in immune cells are generally lower than those in hepatocytes, these DPGs regulate immunological functions and may contribute to the metabolism of toxicants and therapeutics.

It is well-established that hepatocytes exhibit zonal specificity in their metabolic functions (Paris and Henderson, 2022), with most DPGs being more highly expressed in centrilobular hepatocytes (Cunningham and Porat-Shliom, 2021). Similarly, our study showed that DPGs were predominantly enriched in centrilobular hepatocytes (47.2%) compared with periportal hepatocytes (12.3%) among the 195 DPGs analyzed (Fig. 4, Fig. 5, Fig. 6, Fig. 7, Fig. 8, Fig. 9). This distribution aligns with the fact that acetaminophen overdose primarily damages centrilobular hepatocytes due to the high expression of CYP2E1 in these cells (Yoon et al, 2016). Similarly, fibrosis induced by alcoholic liver disease affects centrilobular hepatocytes first, then extends into the midzonal and periportal zones, due to the higher expression of metabolic enzymes for ethanol metabolism in the centrilobular area (Gao and Bataller, 2011; Ohashi et al, 2018). The toxicity from acetaminophen overdose is exacerbated by chronic ethanol consumption, which up-regulates CYP2E1 and CYP3A expression (Sinclair et al, 1998; Hinson et al, 2010). Additionally, carbon tetrachloride is metabolized into trichloromethyl radical by CYP2E1, causing lipid peroxidation in centrilobular hepatocytes (Wong et al, 1998). In comparison, periportal hepatocytes are more susceptible to damage from hepatic inflammation and biliary cirrhosis (Tuñón et al, 2009). Overall, given that many hepatic xenobiotic biotransformation processes depend on hepatocytes, understanding the zonal expression pattern of DPGs in hepatocytes is critical for developing accurate models for pharmacokinetics and toxicokinetics.

The distribution of DPGs in liver cell types and the zonal expression of DPGs in hepatocytes can provide valuable insights into the mechanisms of hepatotoxicity. For example, the chemotherapeutic drug doxorubicin is metabolized by CBR1, which is widely expressed across cell types and is enriched in periportal hepatocytes (Fig. 6A). Doxorubicin can cause drug-induced liver injury, including jaundice, oxidative damage, and acute liver failure (Prasanna et al, 2020). Previous work demonstrated that periportal hepatocytes are more susceptible to doxorubicin toxicity, as evidenced by lactate dehydrogenase release and cell death observed in perfused rat liver treated with doxorubicin (Ganey et al, 1988). Similarly, MTX is a chemotherapeutic and immunosuppressant and is associated with the development of fatty liver, hepatic fibrosis, and cirrhosis (Visser and van der Heijde, 2009). MTX is metabolized by AOX1, which is predominantly expressed in hepatocytes but not specifically enriched in periportal or centrilobular hepatocytes (Fig. 5A). AOX1 converts MTX into 7-hydroxy MTX, a metabolite linked to hepatotoxicity (Smeland et al, 1996; Choughule et al, 2015). The disposition of MTX and its metabolite is significantly influenced by MRP transporters, such as MRP2 and MRP3, which are enriched in centrilobular hepatocytes and are also expressed in nonparenchymal cells (Vlaming et al, 2009; Wang et al, 2018). A prior rat study demonstrated that oral MTX exposure primarily damaged zone 3 hepatocytes (Hall et al, 1991), likely caused by the accumulation of MTX and its metabolites in these cells, particularly when glutathione levels are depleted (Mukherjee et al, 2013). In sepsis, endotoxin has been shown to downregulate NTCP, a transporter enriched in centrilobular hepatocytes (Fig. 8A), and this down-regulation can reduce bile acid uptake (Green et al, 1996; Trauner et al, 1998). Digoxin, a drug that interacts with NTCP, is known to influence the pharmacokinetics and drug-drug interactions (Gozalpour et al, 2014). Additionally, inhibition of BSEP, which is enriched in periportal hepatocytes (Fig. 8A), can result in elevated levels of bile acids such as chenodeoxycholic acid, glycodeoxycholic acid, and deoxycholic acid, leading to cholestasis and hepatotoxicity (Rodrigues et al, 2014). Thus, considering the distribution of DPGs across liver zones can enhance the understanding of local hepatotoxicity mechanisms and help elucidate the pathways underlying drug-induced liver injury.

The findings of the present study are based on mRNA expression in hepatic cell types, and the data used in the present study is up to date with the most current technology for measuring mRNA levels in single cells. Follow-up studies can predict the distribution of DPGs in liver cell types and hepatocyte zones that are context-specific, such as in experiments with drug-induced hepatotoxicity and from toxicant exposures, as well as protein levels in liver cell types from correlating additional datasets and deconvoluting whole liver measurements (Avila Cobos et al, 2020). In addition, future studies could further validate the findings by incorporating quantifications of protein expression and activity, as well as transcription factor binding assays performed in single cells or nuclei. Future studies could improve the inference method in this study by conducting a downsampling analysis and adjusting the threshold value. This would also help generalize the method for use in experimental samples, such as those from toxicant exposure studies and liver injury models. Despite the limitation, the present study has provided valuable insights into the distribution of DPGs in hepatic cell types. A comparison of DPGs between the inferred spatial transcriptomics results and zonation-labeled spatial transcriptomics showed 85%–86% consensus (Supplemental Fig. 1), suggesting that the developed transformation-based application for inferring the zonation in hepatocytes using sc/sn RNA-seq data in hepatocytes offers a reliable starting point for identifying the distribution of DPGs between periportal and centrilobular hepatocytes. The study enhances our understanding by highlighting the heterogeneity of DPG expression in various hepatic cell types. Understanding the expression levels and roles of these hepatic cell types in the biotransformation of drugs, other xenobiotics, and endogenous compounds is critical for future mechanistic investigations of hepatotoxicity and liver diseases, particularly within the context of precision medicine and precision environmental health.

Conflict of interest

The authors declare no conflicts of interest.

Acknowledgments

Financial support

Supported by National Institutes of Health (R01ES031098, R01ES030197, F31DK139707); University of Washington Interdisciplinary Center for Exposures, Diseases, and Environment (EDGE, P30ES007033); Environmental Pathology/Toxicology Training Program (T32ES007032); Environmental Health and Microbiome Research Center (EHMBRACE); UW Magnuson Scholar Award; and Sheldon Murphy Endowment.

Data availability

All data utilized for this study can be found in the Gene Expression Omnibus using accession GSE192742.

Author contributions

Experimental design: Klaassen, Lim.

Data analysis and visualization: Lim.

Manuscript writing: Lim; Cui.

Manuscript editing: Cui, Klaassen.

Footnotes

This article has supplemental material available at dmd.aspetjournals.org.

Contributor Information

Curtis Dean Klaassen, Email: curtisklaassenphd@gmail.com.

Julia Yue Cui, Email: juliacui@uw.edu.

Supplemental material

Supplementary Tables 1-5

mmc1.xlsx^{(51.2KB, xlsx)}

Supplementary Figure 1

mmc2.pdf^{(712.1KB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Tables 1-5

mmc1.xlsx^{(51.2KB, xlsx)}

Supplementary Figure 1

mmc2.pdf^{(712.1KB, pdf)}

Data Availability Statement

All data utilized for this study can be found in the Gene Expression Omnibus using accession GSE192742.

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PERMALINK

Deciphering the cell type-specific and zonal distribution of drug-metabolizing enzymes, transporters, and transcription factors in livers of mice using single-cell transcriptomics

Joe Jongpyo Lim

Curtis Dean Klaassen

Julia Yue Cui

Abstract

Significance Statement

1. Introduction

2. Materials and methods

2.1. Single-cell RNA/nuclei sequencing data processing

2.2. Spatial transcriptomics data processing

2.3. Zonation inference of hepatocytes

3. Results

3.1. Inclusion of multiple digestion methods for sc/sn RNA-Seq data analysis

Table 1.

3.2. Cell type identification using known marker genes

Fig. 1.

3.3. Systematic characterization of the zonal distribution of DPGs in hepatocytes

Fig. 2.

Table 2.

Fig. 3.

3.4. Phase-I drug-metabolizing enzymes

Fig. 4.

3.4.1. Cyp1 family

3.4.2. Cyp2 family

3.4.3. Cyp3 family

3.4.4. Cyp4 family

3.4.5. Bile acid synthetic Cyp enzymes

3.4.6. Other Cyps

3.4.7. Alcohol dehydrogenase

Fig. 5.

3.4.8. Aldh1

3.4.9. Other Aldhs

3.4.10. Aox

3.4.11. Epoxide hydrolases

3.4.12. Flavin-containing monooxygenases

3.4.13. Quinone oxidoreductase

3.4.14. Aldo-keto reductases (Akr)

Fig. 6.

3.4.14. Carbonyl reductases

3.4.15. Carboxylesterases

3.4.16. Paraoxonases

3.5. Phase-II conjugation enzymes

3.5.1. UDP-glucuronosyltransferases

Fig. 7.

3.5.2. Glutathione S-transferases

3.5.3. Sulfotransferases

3.5.4. N-acetyltransferases

3.5.5. Hepatic methyltransferases

3.5.6. Amino acid conjugation enzymes

3.5.7. Cofactor synthetases in hepatic phase-II metabolism

3.6. Transporters

3.6.1. Slco/Oatp transporters

Fig. 8.

3.6.2. Organic anion transporters

3.6.3. Organic cation transporters

3.6.4. Nucleoside transporters

3.6.5. Multidrug and toxin extrusion 1

3.6.6. Multidrug resistance proteins

3.6.7. Multidrug resistance-associated proteins

3.6.8. Breast cancer resistance protein

3.6.9. Bile acid transporters

3.6.10. Cholesterol and lipid transporters and an anion exchanger

3.6.11. Organic solute and steroid transporters

3.7. Transcription factors related to xenobiotic biotransformation

3.7.1. Xenobiotic-sensing transcription factors

Fig. 9.

3.7.2. Fatty acid-sensing nuclear receptors

3.7.3. Nuclear factor erythroid 2-related factor 2

3.7.4. Bile acid-regulating nuclear receptors

3.7.5. Hepatocyte nuclear factor 4a

3.7.6. Liver X receptors β and α

3.7.7. Retinoic acid and related receptors

4. Discussion

Conflict of interest

Acknowledgments

Financial support

Data availability

Author contributions

Footnotes