Vsig4 + Resident Single-Kupffer Cells Improve Hepatic Inflammation and Fibrosis in NASH

doi:10.21203/rs.3.rs-2213699/v1

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Vsig4 + Resident Single-Kupffer Cells Improve Hepatic Inflammation and Fibrosis in NASH

https://doi.org/10.21203/rs.3.rs-2213699/v1

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published 06 Feb, 2023

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The role of macrophages in the pathogenesis of nonalcoholic steatohepatitis (NASH) is complex and unclear. Here, single-cell RNA sequencing was performed on nonparenchymal cells isolated from NASH and control mice. Two main single macrophage subsets were identified that exhibited a significant change in cell percentage when NASH occurred: resident Kupffer cells (KCs; Cluster 2) and lipid-associated macrophages (LAMs; Cluster 13). Nearly 93% of single-LAMs in Cluster 13 specifically expressed Cx3cr1, and an increase in Cx3crl⁺ single-LAMs was speculated to play a proinflammatory role in NASH. Nearly 82% of resident single KCs in Cluster 2 specifically expressed Cd163, and an inhibited subgroup of Cd163⁺ resident single-KCs was suggested to have a protective effect in NASH. Similar to Cd163, Vsig4 was both enriched in and specific to Cluster 2. The percentage of Vsig4⁺-KCs was significantly decreased in NASH in vivo and in vitro. Hepatocytes and hepatic stellate cells produced less lipid droplet accumulation, proinflammatory protein (TNF-α) and profibrotic protein (α-SMA) in response to coculture with Vsig4⁺-KCs than in those cocultured with lipotoxic KCs. Therefore, a subgroup of Vsig4⁺ resident single-KCs was shown to improve hepatic inflammation and fibrosis in NASH.

NASH

non-alcoholic steatohepatitis

macrophages

scRNA-seq

single-cell RNA sequencing

Vsig4

V-set and immunoglobulin domain-containing 4

KCs

Kupffer Cells

Nonalcoholic fatty liver disease (NAFLD) is a major chronic liver disease with an increasing incidence, affecting approximately 1.7 billion people worldwide [1]. Up to one-third of patients with NAFLD can develop nonalcoholic steatohepatitis (NASH), and conversion to NASH is associated with a significantly increased risk of liver fibrosis and liver-related death [2].

Activated macrophages are the first line of defense against hepatocyte damage [3]. Polarization, tissue recruitment, and inflammatory activation of macrophages are critical for the progression of NAFLD, and cytokines (e.g., IL-6, TNFα, and IL-1β) produced by macrophages can directly target hepatocytes to promote steatosis, inflammation, and liver damage [4]. Injured hepatocytes stimulate liver-resident Kupffer cells (KCs) to release proinflammatory cytokines and recruit monocyte-derived macrophages (MDMs), accelerating the progression of NAFLD to NASH and cirrhosis [5].

Single-cell RNA sequencing (scRNA-seq) is a novel technique for amplifying and sequencing whole genomes at the single cell level. Recently, scRNA-seq research has further refined the classification of macrophages and examined the mechanism of macrophages in NASH at the cellular level [6, 7].

In this study, we performed scRNA-seq on liver tissues from NASH mice and normal mice and found that the subset composition of macrophages was changed in NASH. We screened a new subset of Vsig4+ (V-set and immunoglobulin domain-containing 4) macrophages that were significantly reduced in NASH progression and may influence hepatocytes and hepatic stellate cells (HSCs) to exert anti-inflammatory effects.

NASH mouse models

Six male C57BL/6 mice, 8 weeks of age,were randomly fed either a standard diet as a control group or a methionine-choline deficient diet (MCD) as a NASH group for 6 weeks (each group, n = 3) [8]. The Institutional Animal Care and Use Committee of Shanghai East Hospital approved the animal study.

Single-cell RNA-seq

To obtain the transcriptomic expression profile of single cells from liver tissue, a microwell-based BD Rhapsody system (BD, San Jose, CA) was used according to the manufacturer’s protocol [9]. The single-cell transcriptome was used to create a cDNA library containing cell labels and unique molecular identifiers (UMIs). All procedures were performed with a BD Rhapsody cDNA Kit and BD Rhapsody Targeted mRNA & AbSeq Amplification Kit (BD Biosciences).

Clustering analysis and visualization

The Seurat package (version 4.0) was used to integrate all cells across samples. A principal component analysis (PCA) was performed based on the top 2000 highly variable features after log-normalization based on total cellular UMI count and after scaling the data with respect to UMI counts. Clustering was then performed at a resolution of 0.6, and the data were visualized using t-distributed stochastic neighborhood embedding (t-SNE) or uniform manifold approximation and projection (UMAP). Feature plots, violin plots and heatmaps were used to visualize the expression of the indicated genes in each cluster.

Differentially expressed gene (DEG) analysis

Specific markers for each cluster were calculated using the FindAllMarkers function embedded in the Seurat package. Genes were regarded as upregulated when their log2-fold change (logFC) > 0.25 and downregulated when their logFC <-0.25 (adjusted p value < 0.05). The average logFC (avg-logFC) reflected the enrichment of a DEG in each cluster. DEGs with high enrichment were defined as enriched DEGs. The percent FC (pct-FC) was the ratio of the percent DEG expression in one cluster to the percent expression in other clusters, reflecting the specificity of DEG expression in this cluster. DEGs with high specificity were defined as specific DEGs. The ClusterProfiler package was applied to detect enriched Kyoto Encyclopedia of Genes and Genome pathways (KEGG) or Gene Ontology (GO) biological functions from each set of DEGs.

Isolation and culture of mouse primary cells

Primary hepatocytes (PHCs) and primary hepatic macrophages (PHMs) were isolated from C57BL/6 mice using a modified collagenase perfusion method as previously described [10]. Cells were first separated by Percoll gradients (Yeasen Biotech Co., Ltd., Shanghai, China) and then cultured at 37°C with 5% CO₂ for 2 h to allow the macrophages to adhere. After the nonadherent cells were removed, PHMs were collected and cultured in RPMI-1640 media (Gibco, Grand Island, NY, USA) supplemented with 5% FBS, antibiotics and antimycotics (Sigma‒Aldrich, St. Louis, MO, USA). Supplemental Figure S1A shows the microscopic morphology of PHMs cultured for 24 h and 48 h in vitro. PHCs were isolated using a two-step collagenase digestion method and cultured with M199 (Gibco) supplemented with 10% FBS, antibiotics and antimycotics.

Cell line culture and treatment

RAW264.7 cells (mouse macrophages) and LX2 cells (human HSCs) were cultured in DMEM (HyClone South Logan, UT, USA) containing 10% FBS and antibiotics. To obtain lipotoxic macrophages, RAW264.7 cells were treated with palmitic acid (PA, 400 µM; Sigma‒Aldrich) for 6 h (Figure S2B). LX2 cells were treated with transforming growth factor-β1 (TGF-β1, 10 ng/ml; Sigma‒Aldrich) for 24 h.

Flow Cytometry and Vsig4⁺ PHM Sorting

PHMs were harvested after treatment with PA (400 µM, Sigma‒Aldrich) or BSA for 6 h. The cells were then incubated with Alexa Fluor 488-labeled anti-Vsig4 (Table S1; Thermo Fisher Scientific Inc., Waltham, MA, USA) and PE-labeled anti-F4/80 (Table S1; BD Biosciences, Franklin Lakes, NJ, USA). All samples were analyzed with a BD Accuri C6 flow cytometer (BD Biosciences), and FlowJo v10 software (BD Biosciences) was used to analyze the data. This process was repeated three times. To obtain Vsig4⁺ PHMs, cell sorting was performed on isolated PHMs using a BD FACSAria (BD Biosciences) flow cytometer [11].

Coculture experiments

Transwells were used to establish a coculture system. PHMs were seeded on a 0.4 µm Transwell insert (Corning Inc., Corning, NY, USA) and then cocultured with PHCs or LX2 cells for 18 h in a 1:10 ratio. Based on different preprocessing procedures, cells in the upper chamber could be divided into the following 3 groups: (i-ii) PHMs treated with BSA or 400 µM PA for 6 h and (iii) Vsig4⁺ PHMs treated with 400 µM PA for 6 h.

ORO (oil red O) staining and immunohistochemistry (IHC) analyses

After coculture, PHCs were stained with oil red O (ORO). Mouse liver tissue sections were prepared and stained for Vsig4 expression with mouse anti-Vsig4 antibodies (1:100) (Table S1; Thermo Fisher Scientific Inc., Waltham, MA, USA). Tissue morphology was observed through a light microscope (Leica Microsystems, Wetzlar, Germany). This process was repeated three times.

Quantitative real-time PCR (qPCR)

qPCR was performed using a SYBR Green PCR Kit (Yeasen) and an ABI 7900HT Fast Real-Time PCR System (Applied Biosystems, Foster City, CA). The primers (Sangon Biotech Co., Ltd., Shanghai, China) used are listed in Table S2. This process was repeated three times.

Immunofluorescence (IF) assay

For IF staining, cells was incubated with anti-TNF (tumor necrosis factor)-α (Table S1; Abcam, Cambridge, MA, USA) and anti-α-SMA (smooth muscle actin) (Table S1; Abcam) at a 1:200 dilution. Nuclei were visualized using DAPI. Representative images were captured via a TCS SP8 CARS confocal fluorescence microscope (Leica Microsystems). Relative fluorescence values were measured via ImageJ 1.8.0 (Rawak Software Inc., Stuttgart, Germany). This process was repeated three times.

Statistical analysis

SPSS 19.0 software (SPSS Inc., Chicago) was applied to analyze all data presented in this study. Data are expressed as the mean ± SD of three independent experiments for each group. Differences between two groups were analyzed with an unpaired Student’s t test. A p value < 0.05 was considered statistically significant.

Transition and definition of three macrophage subsets in liver tissue of NASH mice

Single cells were isolated from the livers of NASH and control mice, and scRNA-seq was performed on nonparenchymal cells (NPCs). We filtered out cells with unique feature counts < 200 or > 10000, including cells with less than 25% mitochondrial genes (Figure S2A). The t-SNE plot analysis revealed 21 major single cell clusters; 8229 cells were included in our study after quality control filters were applied (Figure S2B). We detected 526 and 589 macrophages in the control group and NASH group, respectively. Three main macrophage subsets (Clusters 2, 13 and 19) were identified based on their expression of cell type-specific markers (Fig. 1A). The percentage of Cluster 2 cells in the NASH group was dramatically decreased compared with that in the control group (NASH, 92.6% vs. CON, 81.7%; Fig. 1B). Cluster 13 was increased from 5.9% in the control group to 14.6% in the NASH group (Fig. 1B). The percentage of Cluster 19 cells was less than 5%, with no difference between the NASH and control groups. The heatmap showed the top 10 specific DEGs of each macrophage cluster (Fig. 1C), indicating that distinct macrophage subsets were identified as defined by scRNA-seq.

Single cells of these 3 clusters highly expressed mouse macrophage marker genes, including Adgre1 (also designated F4/80) and CD68 (Fig. 1D and 1E, respectively). Macrophages are classically divided into the M1 and M2 types, but intrahepatic macrophages can be divided into resident KCs and infiltrative MDMs based on in-depth scRNA-seq research [6]. MDMs are further classified as monocyte-derived Kupffer cells (MoKCs) and lipid-associated macrophages (LAMs) [12]. Cluster 2 and Cluster 19 were enriched in the expression of the KC marker gene Clec4f (Fig. 1F). The marker gene of resident KCs (Timd4) was highly expressed in Cluster 2 (Fig. 1G), whereas the marker genes of LAMs (Cx3cr1 and Ccr2) were highly expressed in Cluster 13 (Fig. 1H and 1I, respectively). Cluster 19 expressed the marker gene of MoKCs (Clec2, Table S3). Therefore, Cluster 2, with a reduced cell percentage in NASH was defined as resident KCs. Cluster 13 and Cluster 19 with elevated cell percentages in NASH were defined as LAMs and MoKCs, respectively. Due to the extremely low proportion of Cluster 19, we mainly focused on Cluster 2 and Cluster 13 for further analysis.

Characteristics and biological functions of LAMs distributed in Cluster 13

The percentage of cells with LAMs in Cluster 13 was significantly elevated in NASH. LAMs in Cluster 13 were characterized by enriched expression of Cx3cr1, Ccr2, Cd93, and Gpnmb in a t-SNE plot analysis (the top 4 enriched DEGs, Fig. 2A). Cx3cr1 and Ccr2 have been found to be associated with inflammatory progression in the liver [13–14]. Cd93 can exert a proinflammatory effect in atherosclerosis [15]. Gpnmb has been identified to have a bidirectional effect on inflammation [16]. All top 4 enriched DEGs in the LAMs of Cluster 13 may participate in the proinflammatory response. The top 10 specific DEGs of Cluster 13, including Tmem119, Runx3, Itga6, Cx3cr1 (Fig. 2B) and six others, were also identified by t-SNE plot analysis (Figure S3A). Interestingly, Cx3cr1 was both specific to and enriched in the LAMs of Cluster 13. Nearly 93.2% of cells in Cluster 13 were Cx3cr1⁺, and the percent fold change (pct-FC) was the 6th highest (Table S4). Except for Cx3cr1, the remaining top 9 specific DEGs were expressed on less than 40% of the single cells in Cluster 13 (Table S4). The GO processes included regulation of tumor necrosis factor production, T-cell activation and regulation of leukocyte differentiation in biological processes (BP); lysosome, MHC protein complex and multivesicular body in cell components (CC); chemokine binding, chemokine binding and MHC protein complex binding in molecular functions (MF) (Fig. 2C). Based on the KEGG pathway enrichment analysis, we identified significantly enriched pathways, including Th1 and Th2 cell differentiation, lipid and atherosclerosis, chemokine, and MAPK signaling pathways (Fig. 2D). The LAMs distributed in Cluster 13 were enriched in the expression of proinflammatory genes such as Cx3cr1, with an increased cell percentage in NASH mice. Their biological functions were associated with the inflammation process, suggesting that this subset may play a proinflammatory role in NASH.

Characteristics and biological functions of resident KCs distributed in Cluster 2

In contrast, the percentage of resident KCs in Cluster 2 was significantly decreased in NASH. Cluster 2 was characterized by enriched expression of Clec4f, Vsig4, Cd163, and C6 using t-SNE plot analysis (the top 4 enriched DEGs, Fig. 3A). Clec4f is one of the characteristic markers of KCs. Cd163 is an M2 macrophage-specific marker, typically representing macrophage activation [17]. Increasing M2 macrophages alleviates hepatic steatosis and NASH [18]. In the immune response, Vsig4 was found to have suppressive and anti-inflammatory effects [19]. In nerve injury, C6 promoted macrophage activation [20]. We identified the top 10 specific DEGs: Cd163, Chp2, Pcolce2, Slc16a9 (Fig. 3B-E) and six other genes of this cluster using t-SNE plot analysis (Figure S3B). The resident single-KCs of Cluster 2 were both specific to and enriched in expressed Cd163. Nearly 82.5% of cells in Cluster 2 expressed Cd163, and pct-FC was the 8th highest (Table S4). In the t-SNE plot analysis, Cd163⁺ resident single-KCs in Cluster 2 were significantly reduced in the NASH group compared with the control group (Fig. 3B). The GO processes included regulation of endocytosis, leukocyte migration and regulation of inflammatory response in BP; lysosome, respiratory chain and cell‒cell junction in CC; and cytochrome-c oxidase activity, cell adhesion molecule binding and proton transmembrane transporter activity in MF (Fig. 3F). Based on the KEGG pathway enrichment analysis, we identified significantly enriched pathways, including fluid shear stress and atherosclerosis, NAFLD and PPAR, RAS, and Rap1 signaling pathways (Fig. 3G). Resident single-KCs distributed in Cluster 2 specifically expressed Cd163, the M2 marker gene, with a markedly decreased cell percentage in NASH mice. Their biological function was related to the improvement of inflammation and lipid metabolism, suggesting that this subset of single-KCs may exert an anti-inflammatory effect in NASH.

Vsig4⁺ resident single-KCs of Cluster 2 were significantly suppressed in NASH

Because Cluster 2, as resident KCs, represented the largest proportion (81.7% in the NASH group) of macrophages, we validated the expression of several top 10 specific DEGs in lipotoxic macrophages using qPCR. Because Timd4 and Cd163 are canonical markers of macrophages, they were not further examined. Based on qPCR, the expression levels of Kcnj16, Chp2, Ccdc148 and Folr2 were markedly decreased in lipotoxic RAW264.7 cells (PA 400 µM treatment for 6 h) compared with control cells (BSA treatment for 6 h) (Fig. 4G-J). The number of these gene-expressing positive single KCs was significantly decreased in the NASH group compared with the control group in the t-SNE plot analysis (Fig. 4B-E). To date, there are no reports on correlations among Kcnj16, Chp2, Ccdc148 and NAFLD. Lake AD indicated that Folr2 could be a diagnostic target of NASH in special imaging and that its expression was elevated in NASH [21]. Therefore, these 4 genes need further elucidation of their concrete mechanisms in NAFLD. We focused on Vsig4. Vsig4 (with the 9th highest pct-FC) was reported to be restricted to tissue macrophages [22] and was expressed by 96.4% of cells in Cluster 2. The t-SNE plot analysis revealed that Vsig4⁺ resident single-KCs were obviously reduced in the NASH group compared with the control group (Fig. 4A). The mRNA expression of Vsig4 was significantly reduced in lipotoxic macrophages (Fig. 4F). Li Y reported that the expression of Vsig4 was significantly downregulated in the livers of NAFLD patients and mice [23], which is consistent with our analysis. Vsig4 was characteristically expressed in the resident KCs of Cluster 2. Vsig4⁺ resident single-KCs were markedly reduced in NASH mice, and decreased expression of Vsig4 was confirmed in lipotoxic macrophages. Therefore, we further investigated the role of Vsig4⁺ resident single-KCs in NASH.

Vsig4⁺-KCs improved hepatic inflammation and fibrosis in NASH

IHC staining of Vsig4 was performed in the liver tissues of control and NASH mice. Vsig4⁺-KCs were concentrated in the pericentral venous region (pericentral region, 14.7% vs. periportal region, 2.9%; p < 0.05, Fig. 5A). The staining area of Vsig4⁺-KCs in NASH mice was much smaller than that in control mice (CON, 7.7% vs. NASH, 2.3%; p < 0.05, Fig. 5B). Flow cytometry revealed an obvious decrease in the percentage of Vsig4⁺-PHMs when pretreated with PA compared with that with BSA (BSA, 39.5% vs. PA, 31.5%; p < 0.05, Fig. 5C). To explore the effect of Vsig4⁺-KCs on liver inflammation and fibrosis, we cocultured PHCs or LX2 cells (HSC line) with BSA-treated PHMs (BSA group), PA-treated PHMs (PA group) or PA-treated Vsig4⁺-PHMs (PA + Vsig4⁺ group) for 24 h. Lipotoxic PHMs significantly increased lipid deposition in PHCs, but Vsig4⁺-PHMs alleviated lipid deposition in PHCs (area ratio of PA group vs. BSA group: 3.06-fold, p < 0.05; PA + Vsig4⁺ group vs. PA group: 0.53-fold, p < 0.05, Fig. 5A). Lipotoxic PHMs significantly increased TNF-α protein (green IF) expression in PHCs, and Vsig4⁺-PHMs decreased TNF-α protein expression in PHCs (IF intensity ratio of PA group vs. BSA group: 5.22-fold, p < 0.05; PA + Vsig4⁺ group vs. PA group: 0.54-fold, p < 0.05, Fig. 5B). Lipotoxic PHMs significantly increased α-SMA protein (red IF) expression of LX2, and Vsig4⁺-PHMs decreased α-SMA protein expression of LX2 (IF intensity ratio of PA group vs. BSA group: 22-fold, p < 0.05; PA + Vsig4⁺ group vs. PA group: 0.32-fold, p < 0.05, Fig. 5C). Vsig4⁺-KCs were distributed in the pericentral venous region and were significantly reduced in NASH. In a lipotoxic environment, Vsig4⁺-KCs can alleviate lipid deposition, inhibit TNF-α expression in hepatocytes and suppress α-SMA expression in HSCs, indicating that Vsig4⁺-KCs have the ability to improve hepatic inflammation and fibrosis in NASH.

NAFLD is one of the major causes of liver disease worldwide and will probably emerge as the leading cause of end-stage liver disease in the coming decades. NAFLD affecting adults and children is often associated with metabolic comorbidity, potentially placing a growing burden on health care and economies [24]. NASH occurs in 2–5% of the general population [25] and is characterized by necroinflammation and a faster fibrosis progression than that of NAFLD [26]. The pathogenesis of NASH is multifactorial and not yet completely understood. Notably, innate immunity is a major contributing factor in which resident KCs and recruited MDMs play a central part in disease progression [25]. In the healthy state, most macrophages in the liver are resident KCs derived from the yolk sac, presenting in the hepatic sinusoids and the space of Disse, and interacting with HSCs, hepatocytes, and liver sinusoidal endothelial cells [12, 27]. However, during the progression of NASH, a large number of MDMs from the bone marrow infiltrate the liver, which has proinflammatory effects that aggravate liver injury [28]. One portion of the MDMs evolves into MoKCs that fill the niche of progressively dying resident KCs and persists in the liver, and another portion evolves into LAMs [28]. LAMs exhibit greater transcriptional alterations and lower lipid storage efficiency than resident KCs [12].

The biological heterogeneity and interactions between recruited MDMs and resident KCs in NASH have been difficult to resolve, and traditional M1 and M2 nomenclature fails to adequately describe the diversity of macrophage phenotypes. In recent years, the heterogeneity and dynamic transition of macrophages in NASH has been more successfully investigated using scRNA-seq [29]. Xiong reported that over 93% of Trem2^hi-KC cells were derived from NASH livers, indicating that this was a unique macrophage subset associated with NASH pathogenesis [6]. Sabine described a reduction in mature Timd4⁺ KCs and the accumulation of monocyte-derived Timd4⁻ macrophages in the livers of NASH mice [29]. In this study, we collected liver tissues from NASH and control mice to isolate single cells and perform scRNA-seq. Ultimately, 8229 NPCs were included in the data analysis, and 21 major cell clusters were found based on cell-specific markers. Macrophages, as the second largest proportion of NPCs, could be divided into 3 main clusters with a total of 1115 cells. Consistent with previous reports [12], these 3 clusters were identified as resident KCs (Cluster 2), LAMs (Cluster 13) and MoKCs (Cluster 19).

We focused on representative DEGs and GO and KEGG enrichment of Clusters 2 and 13. First, the features of single-LAMs in Cluster 13 were described. In NASH mouse livers, the proportion of single-LAMs in Cluster 13 was obviously increased. Cx3cr1 (a chemokine receptor of fractalkine), which is related to hepatic fat accumulation and liver damage in NAFLD [30–31], is a specific marker for LAMs [12]. In our study, nearly 93% of single-LAMs in Cluster 13 specifically expressed Cx3cr1. The cell functions of Cluster 13 were mainly involved in tumor necrosis factor production and chemokine binding. Based on KEGG enrichment, Cluster 13 may exert proinflammatory effects via the MAPK pathway to exacerbate NASH. Zhang demonstrated that MAPK could promote nutritional steatohepatitis through M1 polarization [32]. Therefore, we speculated that increasing Cx3crl⁺ single-LAMs distributed in Cluster 13 would play a proinflammatory role in NASH. Although in NASH mouse livers the proportion of resident single KCs of Cluster 2 was markedly decreased, it remained the dominant macrophage subset. Nearly 82% of resident single KCs in Cluster 2 specifically expressed Cd163, which is an M2 macrophage-specific marker [17]. The single KCs of Cluster 2 were identified by the general expression of Timd4, which is the marker gene of resident KCs [33]. Cd163 was then found to be more suitable for labeling resident single KCs with high specificity and enrichment in Cluster 2. The cell functions of Cluster 2 may be related to endocytosis and the inflammatory response. Based on KEGG enrichment, the PPAR pathway was found to be the most dysregulated, which has been indicated to ameliorate NAFLD by activating macrophages [34]. Therefore, an inhibited subgroup of Cd163⁺ resident single-KCs was selected and suggested to have a protective effect in NASH.

Cluster 2 expressed other specific DEGs, including Kcnj16, Chp2, Ccdc148, Vsig4 and Folr2, which were all downregulated in lipotoxic macrophages. Vsig4 is a membrane protein that belongs to the complement receptor of the immunoglobulin superfamily [19]. Vsig4⁺ KCs can induce and maintain immune tolerance in hepatic T and NKT cells, and Vsig4 had therapeutic effects on immune-mediated liver injury [35]. Clearance of microbiota-derived products from the bloodstream by Vsig4⁺ KCs in mouse livers ameliorated the development of obesity-related tissue inflammation and metabolic disease [36]. Notably, in our study, similar to Cd163, Vsig4 was enriched in and specific to Cluster 2. Nearly 96% of single cells in Cluster 2 were Vsig4⁺, and the percent fold change (pct-FC) was the 9th highest. Vsig4⁺-KCs were mainly concentrated in the pericentral venous region and obviously decreased in liver tissues of NASH mice (MCD induced). Moreover, the lipotoxic environment dramatically decreased the number of Vsig4⁺ primary KCs. Interestingly, HCs and HSCs produced less lipid droplet accumulation, and proinflammatory protein (TNF-α) and profibrotic protein (α-SMA) responded to coculture with Vsig4⁺-KCs compared with those cocultured with KCs under PA stimulation. Taken together, these studies demonstrate that Vsig4⁺-KCs may ameliorate NASH by influencing hepatocytes or HSCs in a lipotoxic environment. The dynamic reduction in the percentage of Vsig4⁺-KCs in NASH may be one of the factors driving disease progression.

In short, by using scRNA-seq, we revealed the heterogeneity and transformation of two single macrophage subsets in NASH mice based on the enrichment of DEGs, GO and KEGG. Furthermore, a group of Vsig4 ⁺ resident single-KCs was shown to improve hepatic inflammation and fibrosis in NASH.

Conflict of interests

There are no conflicts of interest.

Authors’ contributions

Conceived the study design: M.Y.X. and Z.H.L.

Performed the experiments and analyzed the data: H.Y.L., S.W.F and J.C.W.

Analyzed the scRNA-seq data set: H.Y.L. and Z.H.L.

Wrote the article: H.Y.L. and M.Y.X.

Acknowledgments

This study was supported by the National Natural Science Foundation of China (No. 82270604, 82200629, 82100607), Shanghai East hospital talent introduction project (202106) and the National 13th Five-Year Major Project (No.2017ZX10203202-003). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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No competing interests reported.

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Journal Publication

published 06 Feb, 2023

Read the published version in Inflammation Research →

Editorial decision: Accepted
20 Jan, 2023
Reviews received at journal
20 Jan, 2023
Reviewers agreed at journal
31 Dec, 2022
Reviewers invited by journal
08 Nov, 2022
Submission checks completed at journal
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You are reading this latest preprint version

Vsig4 + Resident Single-Kupffer Cells Improve Hepatic Inflammation and Fibrosis in NASH

Status:

Journal Publication

Version 1

Abstract

Figures

Introduction

Methods And Materials

NASH mouse models

Single-cell RNA-seq

Clustering analysis and visualization

Differentially expressed gene (DEG) analysis

Isolation and culture of mouse primary cells

Cell line culture and treatment

Flow Cytometry and Vsig4⁺ PHM Sorting

Coculture experiments

ORO (oil red O) staining and immunohistochemistry (IHC) analyses

Quantitative real-time PCR (qPCR)

Immunofluorescence (IF) assay

Statistical analysis

Results

Transition and definition of three macrophage subsets in liver tissue of NASH mice

Characteristics and biological functions of LAMs distributed in Cluster 13

Characteristics and biological functions of resident KCs distributed in Cluster 2

Vsig4⁺ resident single-KCs of Cluster 2 were significantly suppressed in NASH

Vsig4⁺-KCs improved hepatic inflammation and fibrosis in NASH

Discussion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1

Vsig4 + Resident Single-Kupffer Cells Improve Hepatic Inflammation and Fibrosis in NASH

Status:

Journal Publication

Version 1

Abstract

Figures

Introduction

Methods And Materials

NASH mouse models

Single-cell RNA-seq

Clustering analysis and visualization

Differentially expressed gene (DEG) analysis

Isolation and culture of mouse primary cells

Cell line culture and treatment

Flow Cytometry and Vsig4+ PHM Sorting

Coculture experiments

ORO (oil red O) staining and immunohistochemistry (IHC) analyses

Quantitative real-time PCR (qPCR)

Immunofluorescence (IF) assay

Statistical analysis

Results

Transition and definition of three macrophage subsets in liver tissue of NASH mice

Characteristics and biological functions of LAMs distributed in Cluster 13

Characteristics and biological functions of resident KCs distributed in Cluster 2

Vsig4+ resident single-KCs of Cluster 2 were significantly suppressed in NASH

Vsig4+-KCs improved hepatic inflammation and fibrosis in NASH

Discussion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1

Flow Cytometry and Vsig4⁺ PHM Sorting

Vsig4⁺ resident single-KCs of Cluster 2 were significantly suppressed in NASH

Vsig4⁺-KCs improved hepatic inflammation and fibrosis in NASH