Single-Cell, Single-Nucleus, and Spatial RNA Sequencing of the Human Liver Identifies Cholangiocyte and Mesenchymal Heterogeneity

New discoveries in the field of metabolism by applying single-cell and spatial omics

Single-cell multi-Omics (SCM-Omics) and spatial multi-Omics (SM-Omics) technologies provide state-of-the-art methods for exploring the composition and function of cell types in tissues/organs. Since its emergence in 2009, single-cell RNA sequencing (scRNA-seq) has yielded many groundbreaking new discoveries. The combination of this method with the emergence and development of SM-Omics techniques has been a pioneering strategy in neuroscience, developmental biology, and cancer research, especially for assessing tumor heterogeneity and T-cell infiltration. In recent years, the application of these methods in the study of metabolic diseases has also increased. The emerging SCM-Omics and SM-Omics approaches allow the molecular and spatial analysis of cells to explore regulatory states and determine cell fate, and thus provide promising tools for unraveling heterogeneous metabolic processes and making them amenable to intervention. Here, we review the evolution of SCM-Omics and SM-Omics technologies, and describe the progress in the application of SCM-Omics and SM-Omics in metabolism-related diseases, including obesity, diabetes, nonalcoholic fatty liver disease (NAFLD) and cardiovascular disease (CVD). We also conclude that the application of SCM-Omics and SM-Omics approaches can help resolve the molecular mechanisms underlying the pathogenesis of metabolic diseases in the body and facilitate therapeutic measures for metabolism-related diseases. This review concludes with an overview of the current status of this emerging field and the outlook for its future.

New therapeutic concepts against ischemia-reperfusion injury in organ transplantation

INTRODUCTION

Ischemia-reperfusion injury (IRI) involves a positive amplification feedback loop that stimulates innate immune-driven tissue damage associated with organ procurement from deceased donors and during transplantation surgery. As our appreciation of its basic immune mechanisms has improved in recent years, translating putative biomarkers into therapeutic interventions in clinical transplantation remains challenging.

AREAS COVERED

This review presents advances in translational/clinical studies targeting immune responses to reactive oxygen species in IRI-stressed solid organ transplants, especially livers. Here we focus on novel concepts to rejuvenate suboptimal donor organs and improve transplant function using pharmacologic and machine perfusion (MP) strategies. Cellular damage induced by cold ischemia/warm reperfusion and the latest mechanistic insights into the microenvironment's role that leads to reperfusion-induced sterile inflammation is critically discussed.

EXPERT OPINION

Efforts to improve clinical outcomes and increase the donor organ pool will depend on improving donor management and our better appreciation of the complex mechanisms encompassing organ IRI that govern the innate-adaptive immune interface triggered in the peritransplant period and subsequent allo-Ag challenge. Computational techniques and deep machine learning incorporating the vast cellular and molecular mechanisms will predict which peri-transplant signals and immune interactions are essential for improving access to the long-term function of life-saving transplants.

Human resident liver myeloid cells protect against metabolic stress in obesity

Although multiple populations of macrophages have been described in the human liver, their function and turnover in patients with obesity at high risk of developing non-alcoholic fatty liver disease (NAFLD) and cirrhosis are currently unknown. Herein, we identify a specific human population of resident liver myeloid cells that protects against the metabolic impairment associated with obesity. By studying the turnover of liver myeloid cells in individuals undergoing liver transplantation, we find that liver myeloid cell turnover differs between humans and mice. Using single-cell techniques and flow cytometry, we determine that the proportion of the protective resident liver myeloid cells, denoted liver myeloid cells 2 (LM2), decreases during obesity. Functional validation approaches using human 2D and 3D cultures reveal that the presence of LM2 ameliorates the oxidative stress associated with obese conditions. Our study indicates that resident myeloid cells could be a therapeutic target to decrease the oxidative stress associated with NAFLD.

Single-cell and spatiotemporal transcriptomic analyses reveal the effects of microorganisms on immunity and metabolism in the mouse liver

The gut-liver axis is a complex bidirectional communication pathway between the intestine and the liver in which microorganisms and their metabolites flow from the intestine through the portal vein to the liver and influence liver function. In a sterile environment, the phenotype or function of the liver is altered, but few studies have investigated the specific cellular and molecular effects of microorganisms on the liver. To this end, we constructed single-cell and spatial transcriptomic (ST) profiles of germ-free (GF) and specific-pathogen-free (SPF) mouse livers. Single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq) revealed that the ratio of most immune cells was altered in the liver of GF mice; in particular, natural killer T (NKT) cells, IgA plasma cells (IgAs) and Kupffer cells (KCs) were significantly reduced in GF mice. Spatial enhanced resolution omics sequencing (Stereo-seq) confirmed that microorganisms mediated the accumulation of Kupffer cells in the periportal zone. Unexpectedly, IgA plasma cells were more numerous and concentrated in the periportal vein in liver sections from SPF mice but less numerous and scattered in GF mice. ST technology also enables the precise zonation of liver lobules into eight layers and three patterns based on the gene expression level in each layer, allowing us to further investigate the effects of microbes on gene zonation patterns and functions. Furthermore, untargeted metabolism experiments of the liver revealed that the propionic acid levels were significantly lower in GF mice, and this reduction may be related to the control of genes involved in bile acid and fatty acid metabolism. In conclusion, the combination of sc/snRNA-seq, Stereo-seq, and untargeted metabolomics revealed immune system defects as well as altered bile acid and lipid metabolic processes at the single-cell and spatial levels in the livers of GF mice. This study will be of great value for understanding host-microbiota interactions.

Characterization and Optimization of Multiomic Single-Cell Epigenomic Profiling

The snATAC + snRNA platform allows epigenomic profiling of open chromatin and gene expression with single-cell resolution. The most critical assay step is to isolate high-quality nuclei to proceed with droplet-base single nuclei isolation and barcoding. With the increasing popularity of multiomic profiling in various fields, there is a need for optimized and reliable nuclei isolation methods, mainly for human tissue samples. Herein we compared different nuclei isolation methods for cell suspensions, such as peripheral blood mononuclear cells (PBMC, n = 18) and a solid tumor type, ovarian cancer (OC, n = 18), derived from debulking surgery. Nuclei morphology and sequencing output parameters were used to evaluate the quality of preparation. Our results show that NP-40 detergent-based nuclei isolation yields better sequencing results than collagenase tissue dissociation for OC, significantly impacting cell type identification and analysis. Given the utility of applying such techniques to frozen samples, we also tested frozen preparation and digestion (n = 6). A paired comparison between frozen and fresh samples validated the quality of both specimens. Finally, we demonstrate the reproducibility of scRNA and snATAC + snRNA platform, by comparing the gene expression profiling of PBMC. Our results highlight how the choice of nuclei isolation methods is critical for obtaining quality data in multiomic assays. It also shows that the measurement of expression between scRNA and snRNA is comparable and effective for cell type identification.

Sample size calculation for a NanoString GeoMx spatial transcriptomics experiment to study predictors of fibrosis progression in non-alcoholic fatty liver disease

Sample size calculation for spatial transcriptomics is a novel and understudied research topic. Prior publications focused on powering spatial transcriptomics studies to detect specific cell populations or spatially variable expression patterns on tissue slides. However, power calculations for translational or clinical studies often relate to the difference between patient groups, and this is poorly described in the literature. Here, we present a stepwise process for sample size calculation to identify predictors of fibrosis progression in non-alcoholic fatty liver disease as a case study. We illustrate how to infer study hypothesis from prior bulk RNA-sequencing data, gather input requirements and perform a simulation study to estimate required sample size to evaluate gene expression differences between patients with stable fibrosis and fibrosis progressors with NanoString GeoMx Whole Transcriptome Atlas assay.

In Vivo and In Vitro Models to Study Liver Fibrosis: Mechanisms and Limitations

Liver fibrosis is a common result of liver injury owing to various kinds of chronic liver diseases. A deeper understanding of the pathophysiology of liver fibrosis and identifying potential therapeutic targets of liver fibrosis is important because liver fibrosis may progress to advanced liver diseases, such as cirrhosis and hepatocellular carcinoma. Despite numerous studies, the underlying mechanisms of liver fibrosis remain unclear. Mechanisms of the development and progression of liver fibrosis differ according to etiologies. Therefore, appropriate liver fibrosis models should be selected according to the purpose of the study and the type of underlying disease. Many in vivo animal and in vitro models have been developed to study liver fibrosis. However, there are no perfect preclinical models for liver fibrosis. In this review, we summarize the current in vivo and in vitro models for studying liver fibrosis and highlight emerging in vitro models, including organoids and liver-on-a-chip models. In addition, we discuss the mechanisms and limitations of each model.

Hepatic stellate cells maintain liver homeostasis through paracrine neurotrophin-3 signaling that induces hepatocyte proliferation

Organ size is maintained by the controlled proliferation of distinct cell populations. In the mouse liver, hepatocytes in the midlobular zone that are positive for cyclin D1 (CCND1) repopulate the parenchyma at a constant rate to preserve liver mass. Here, we investigated how hepatocyte proliferation is supported by hepatic stellate cells (HSCs), pericytes that are in close proximity to hepatocytes. We used T cells to ablate nearly all HSCs in the murine liver, enabling the unbiased characterization of HSC functions. In the normal liver, complete loss of HSCs persisted for up to 10 weeks and caused a gradual reduction in liver mass and in the number of CCND1+ hepatocytes. We identified neurotrophin-3 (Ntf-3) as an HSC-produced factor that induced the proliferation of midlobular hepatocytes through the activation of tropomyosin receptor kinase B (TrkB). Treating HSC-depleted mice with Ntf-3 restored CCND1+ hepatocytes in the midlobular region and increased liver mass. These findings establish that HSCs form the mitogenic niche for midlobular hepatocytes and identify Ntf-3 as a hepatocyte growth factor.

Single-nucleus RNA sequencing of pre-malignant liver reveals disease-associated hepatocyte state with HCC prognostic potential

Current approaches to staging chronic liver diseases have limited utility for predicting liver cancer risk. Here, we employed single-nucleus RNA sequencing (snRNA-seq) to characterize the cellular microenvironment of healthy and pre-malignant livers using two distinct mouse models. Downstream analyses unraveled a previously uncharacterized disease-associated hepatocyte (daHep) transcriptional state. These cells were absent in healthy livers but increasingly prevalent as chronic liver disease progressed. Copy number variation (CNV) analysis of microdissected tissue demonstrated that daHep-enriched regions are riddled with structural variants, suggesting these cells represent a pre-malignant intermediary. Integrated analysis of three recent human snRNA-seq datasets confirmed the presence of a similar phenotype in human chronic liver disease and further supported its enhanced mutational burden. Importantly, we show that high daHep levels precede carcinogenesis and predict a higher risk of hepatocellular carcinoma development. These findings may change the way chronic liver disease patients are staged, surveilled, and risk stratified.

Integrating Spatial Transcriptomics and Single-nucleus RNA Sequencing Reveals the Potential Therapeutic Strategies for Uterine Leiomyoma

Uterine leiomyoma is the most common gynecological tumor in reproductive women. Tumor-host interface is a complex ecosystem with intimate cell-cell communications and a critical scenario for tumor pathogenesis and progression. The pseudocapsule is the main tumor-host interface of uterine leiomyoma, but its cellular spatial disposition and gene expression are poorly explored. This study mapped the cellular architecture and corresponding gene profiles of the leiomyoma and its surrounding pseudocapsule by integrating spatial transcriptomics and single-nucleus RNA-sequencing at the first time. Here, we reported that estrogen receptor alpha and progesterone receptor mediated the occurrence and development of uterine leiomyoma and that estrogen receptor beta involved in the angiogenesis, which explained the effectiveness of hormonotherapy. Therapeutic targets including ERK1/ERK2 pathway and IGF1-IGF1R were found and might be applied for non-hormonal therapy of uterine leiomyoma. Furthermore, the injection of prostaglandin E2 was initially presented for bleeding control during myomectomy, injection site should be located at the junction between pseudocapsule and leiomyoma, and surrounding pseudocapsule should not be eliminated. Collectively, a single-cell and spatially resolved atlas of human uterine leiomyoma and its surrounding pseudocapsule was established. The results revealed potentially feasible strategies for hormonotherapy, non-hormonal targeted therapy and bleeding control during myomectomy.

Spatiotemporal Characterization of Human Early Intervertebral Disc Formation at Single-Cell Resolution

The intervertebral disc (IVD) acts as a fibrocartilaginous joint to anchor adjacent vertebrae. Although several studies have demonstrated the cellular heterogeneity of adult mature IVDs, a single-cell transcriptomic atlas mapping early IVD formation is still lacking. Here, the authors generate a spatiotemporal and single cell-based transcriptomic atlas of human IVD formation at the embryonic stage and a comparative mouse transcript landscape. They identify two novel human notochord (NC)/nucleus pulposus (NP) clusters, SRY-box transcription factor 10 (SOX10)⁺ and cathepsin K (CTSK)⁺ , that are distributed in the early and late stages of IVD formation and they are validated by lineage tracing experiments in mice. Matrisome NC/NP clusters, T-box transcription factor T (TBXT)⁺ and CTSK⁺ , are responsible for the extracellular matrix homeostasis. The IVD atlas suggests that a subcluster of the vertebral chondrocyte subcluster might give rise to an inner annulus fibrosus of chondrogenic origin, while the fibroblastic outer annulus fibrosus preferentially expresseds transgelin and fibromodulin . Through analyzing intercellular crosstalk, the authors further find that notochordal secreted phosphoprotein 1 (SPP1) is a novel cue in the IVD microenvironment, and it is associated with IVD development and degeneration. In conclusion, the single-cell transcriptomic atlas will be leveraged to develop preventative and regenerative strategies for IVD degeneration.

Identification of a broadly fibrogenic macrophage subset induced by type 3 inflammation

Macrophages are central orchestrators of the tissue response to injury, with distinct macrophage activation states playing key roles in fibrosis progression and resolution. Identifying key macrophage populations found in human fibrotic tissues could lead to new treatments for fibrosis. Here, we used human liver and lung single-cell RNA sequencing datasets to identify a subset of CD9⁺TREM2⁺ macrophages that express SPP1, GPNMB, FABP5, and CD63. In both human and murine hepatic and pulmonary fibrosis, these macrophages were enriched at the outside edges of scarring and adjacent to activated mesenchymal cells. Neutrophils expressing MMP9, which participates in the activation of TGF-β1, and the type 3 cytokines GM-CSF and IL-17A coclustered with these macrophages. In vitro, GM-CSF, IL-17A, and TGF-β1 drive the differentiation of human monocytes into macrophages expressing scar-associated markers. Such differentiated cells could degrade collagen IV but not collagen I and promote TGF-β1-induced collagen I deposition by activated mesenchymal cells. In murine models blocking GM-CSF, IL-17A or TGF-β1 reduced scar-associated macrophage expansion and hepatic or pulmonary fibrosis. Our work identifies a highly specific macrophage population to which we assign a profibrotic role across species and tissues. It further provides a strategy for unbiased discovery, triage, and preclinical validation of therapeutic targets based on this fibrogenic macrophage population.

Cell-matrix interactions control biliary organoid polarity, architecture, and differentiation

BACKGROUND AND AIMS

Cholangiopathies are an important cause of morbidity and mortality. Their pathogenesis and treatment remain unclear in part because of the lack of disease models relevant to humans. Three-dimensional biliary organoids hold great promise; however, the inaccessibility of their apical pole and the presence of extracellular matrix (ECM) limits their application. We hypothesized that signals coming from the extracellular matrix regulate organoids' 3-dimensional architecture and could be manipulated to generate novel organotypic culture systems.

APPROACH AND RESULTS

Biliary organoids were generated from human livers and grown embedded into Culturex Basement Membrane Extract as spheroids around an internal lumen (EMB). When removed from the EMC, biliary organoids revert their polarity and expose the apical membrane on the outside (AOOs). Functional, immunohistochemical, and transmission electron microscope studies, along with bulk and single-cell transcriptomic, demonstrate that AOOs are less heterogeneous and show increased biliary differentiation and decreased expression of stem cell features. AOOs transport bile acids and have competent tight junctions. When cocultured with liver pathogenic bacteria (Enterococcus spp.), AOOs secrete a range of proinflammatory chemokines (ie, MCP1, IL8, CCL20, and IP-10). Transcriptomic analysis and treatment with a beta-1-integrin blocking antibody identified beta-1-integrin signaling as a sensor of the cell-extracellular matrix interaction and a determinant of organoid polarity.

CONCLUSIONS

This novel organoid model can be used to study bile transport, interactions with pathobionts, epithelial permeability, cross talk with other liver and immune cell types, and the effect of matrix changes on the biliary epithelium and obtain key insights into the pathobiology of cholangiopathies.

Sterile liver injury induces a protective tissue-resident cDC1-ILC1 circuit through cDC1-intrinsic cGAS-STING-dependent IL-12 production

Tissue-resident immune cells are critical to the initiation and potentiation of inflammation. However, the tissue-protective cellular communication networks initiated by resident immunity during sterile inflammation are not well understood. Using single-cell transcriptomic analysis, we show the liver-resident cell connectome and signalome during acute liver injury. These analyses identify Il12b as a central regulator of liver injury-associated changes in gene expression. Interleukin (IL)-12 produced by conventional type 1 dendritic cells (cDC1s) is required for protection during acute injury through activation of interferon (IFN)-γ production by liver-resident type 1 innate lymphoid cells (ILC1s). Using a targeted in vivo CRISPR-Cas9 screen of innate immune sensing pathways, we find that cDC1-intrinsic cGAS-STING signaling acts upstream of IL-12 production to initiate early protective immune responses. Our study identifies the core communication hubs initiated by tissue-resident innate immune cells during sterile inflammation in vivo and implicates cDC1-derived IL-12 as an important regulator of this process.

A comparative performance evaluation of imputation methods in spatially resolved transcriptomics data

Spatially resolved transcriptomics technologies have drawn enormous attention by providing RNA expression patterns together with their spatial information. Even though improved techniques are being developed rapidly, the technologies which give spatially whole transcriptome level profiles suffer from dropout problems because of the low capture rate. Imputation of missing data is one strategy to eliminate this technical problem. We evaluated the imputation performance of five available methods (SpaGE, stPlus, gimVI, Tangram and stLearn) which were indicated as capable of making predictions for the dropouts in spatially resolved transcriptomics datasets. The evaluation was performed qualitatively via visualization of the predictions against the original values and quantitatively with Pearson's correlation coefficient, cosine similarity, root mean squared log-error, Silhouette Index and Calinski Harabasz Index. We found that stPlus and gimVI outperform the other three. However, the performance of all methods was lower than expected which indicates that there is still a gap for imputation tools dealing with dropout events in spatially resolved transcriptomics.

Hepatocytes demarcated by EphB2 contribute to the progression of nonalcoholic steatohepatitis

Current therapeutic strategies for treating nonalcoholic steatohepatitis (NASH) have failed to alleviate liver fibrosis, which is a devastating feature leading to hepatic dysfunction. Here, we integrated single-nucleus transcriptomics and epigenomics to characterize all major liver cell types during NASH development in mice and humans. The bifurcation of hepatocyte trajectory with NASH progression was conserved between mice and humans. At the nonalcoholic fatty liver (NAFL) stage, hepatocytes exhibited metabolic adaptation, whereas at the NASH stage, a subset of hepatocytes was enriched for the signatures of cell adhesion and migration, which were mainly demarcated by receptor tyrosine kinase ephrin type B receptor 2 (EphB2). EphB2, acting as a downstream effector of Notch signaling in hepatocytes, was sufficient to induce cell-autonomous inflammation. Knockdown of Ephb2 in hepatocytes ameliorated inflammation and fibrosis in a mouse model of NASH. Thus, EphB2-expressing hepatocytes contribute to NASH progression and may serve as a potential therapeutic target.

Isolation of Nuclei from Human Snap-frozen Liver Tissue for Single-nucleus RNA Sequencing

Single-nucleus RNA sequencing (snRNA-seq) provides a powerful tool for studying cell type composition in heterogenous tissues. The liver is a vital organ composed of a diverse set of cell types; thus, single-cell technologies could greatly facilitate the deconvolution of liver tissue composition and various downstream omics analyses at the cell-type level. Applying single-cell technologies to fresh liver biopsies can, however, be very challenging, and snRNA-seq of snap-frozen liver biopsies requires some optimization given the high nucleic acid content of the solid liver tissue. Therefore, an optimized protocol for snRNA-seq specifically targeted for the use of frozen liver samples is needed to improve our understanding of human liver gene expression at the cell-type resolution. We present a protocol for performing nuclei isolation from snap-frozen liver tissues, as well as guidance on the application of snRNA-seq. We also provide guidance on optimizing the protocol to different tissue and sample types.

Recent Advances in Intrahepatic Biliary Epithelial Heterogeneity

Biliary epithelium (i.e., cholangiocytes) is a heterogeneous population of epithelial cells in the liver, which line small and large bile ducts and have individual responses and functions dependent on size and location in the biliary tract. We discuss the recent findings showing that the intrahepatic biliary tree is heterogeneous regarding (1) morphology and function, (2) hormone expression and signaling (3), response to injury, and (4) roles in liver regeneration. This review overviews the significant characteristics and differences of the small and large cholangiocytes. Briefly, it outlines the in vitro and in vivo models used in the heterogeneity evaluation. In conclusion, future studies addressing biliary heterogeneity's role in the pathogenesis of liver diseases characterized by ductular reaction may reveal novel therapeutic approaches.

Spatiotemporal Metabolic Liver Zonation and Consequences on Pathophysiology

Hepatocytes are the main workers in the hepatic factory, managing metabolism of nutrients and xenobiotics, production and recycling of proteins, and glucose and lipid homeostasis. Division of labor between hepatocytes is critical to coordinate complex complementary or opposing multistep processes, similar to distributed tasks at an assembly line. This so-called metabolic zonation has both spatial and temporal components. Spatial distribution of metabolic function in hepatocytes of different lobular zones is necessary to perform complex sequential multistep metabolic processes and to assign metabolic tasks to the right environment. Moreover, temporal control of metabolic processes is critical to align required metabolic processes to the feeding and fasting cycles. Disruption of this complex spatiotemporal hepatic organization impairs key metabolic processes with both local and systemic consequences. Many metabolic diseases, such as nonalcoholic steatohepatitis and diabetes, are associated with impaired metabolic liver zonation. Recent technological advances shed new light on the spatiotemporal gene expression networks controlling liver function and how their deregulation may be involved in a large variety of diseases. We summarize the current knowledge about spatiotemporal metabolic liver zonation and consequences on liver pathobiology.

TCDD dysregulation of lncRNA expression, liver zonation and intercellular communication across the liver lobule

The persistent environmental aryl hydrocarbon receptor agonist and hepatotoxin TCDD (2,3,7,8-tetrachlorodibenzo- p -dioxin) induces hepatic lipid accumulation (steatosis), inflammation (steatohepatitis) and fibrosis. Thousands of liver-expressed, nuclear-localized lncRNAs with regulatory potential have been identified; however, their roles in TCDD-induced hepatoxicity and liver disease are unknown. We analyzed single nucleus (sn)RNA-seq data from control and chronic TCDD-exposed mouse liver to determine liver cell-type specificity, zonation and differential expression profiles for thousands of IncRNAs. TCDD dysregulated >4,000 of these lncRNAs in one or more liver cell types, including 684 lncRNAs specifically dysregulated in liver non-parenchymal cells. Trajectory inference analysis revealed major disruption by TCDD of hepatocyte zonation, affecting >800 genes, including 121 IncRNAs, with strong enrichment for lipid metabolism genes. TCDD also dysregulated expression of >200 transcription factors, including 19 Nuclear Receptors, most notably in hepatocytes and Kupffer cells. TCDD-induced changes in cellâ€"cell communication patterns included marked decreases in EGF signaling from hepatocytes to non-parenchymal cells and increases in extracellular matrix-receptor interactions central to liver fibrosis. Gene regulatory networks constructed from the snRNA-seq data identified TCDD-exposed liver network-essential lncRNA regulators linked to functions such as fatty acid metabolic process, peroxisome and xenobiotic metabolic. Networks were validated by the striking enrichments that predicted regulatory IncRNAs showed for specific biological pathways. These findings highlight the power of snRNA-seq to discover functional roles for many xenobiotic-responsive lncRNAs in both hepatocytes and liver non-parenchymal cells and to elucidate novel aspects of foreign chemical-induced hepatotoxicity and liver disease, including dysregulation of intercellular communication within the liver lobule.

Perspectives on single-nucleus RNA sequencing in different cell types and tissues

Single-cell RNA sequencing has become a powerful and essential tool for delineating cellular diversity in normal tissues and alterations in disease states. For certain cell types and conditions, there are difficulties in isolating intact cells for transcriptome profiling due to their fragility, large size, tight interconnections, and other factors. Single-nucleus RNA sequencing (snRNA-seq) is an alternative or complementary approach for cells that are difficult to isolate. In this review, we will provide an overview of the experimental and analysis steps of snRNA-seq to understand the methods and characteristics of general and tissue-specific snRNA-seq data. Knowing the advantages and limitations of snRNA-seq will increase its use and improve the biological interpretation of the data generated using this technique.

Biology-inspired data-driven quality control for scientific discovery in single-cell transcriptomics

BACKGROUND

Quality control (QC) of cells, a critical first step in single-cell RNA sequencing data analysis, has largely relied on arbitrarily fixed data-agnostic thresholds applied to QC metrics such as gene complexity and fraction of reads mapping to mitochondrial genes. The few existing data-driven approaches perform QC at the level of samples or studies without accounting for biological variation.

RESULTS

We first demonstrate that QC metrics vary with both tissue and cell types across technologies, study conditions, and species. We then propose data-driven QC (ddqc), an unsupervised adaptive QC framework to perform flexible and data-driven QC at the level of cell types while retaining critical biological insights and improved power for downstream analysis. ddqc applies an adaptive threshold based on the median absolute deviation on four QC metrics (gene and UMI complexity, fraction of reads mapping to mitochondrial and ribosomal genes). ddqc retains over a third more cells when compared to conventional data-agnostic QC filters. Finally, we show that ddqc recovers biologically meaningful trends in gradation of gene complexity among cell types that can help answer questions of biological interest such as which cell types express the least and most number of transcripts overall, and ribosomal transcripts specifically.

CONCLUSIONS

ddqc retains cell types such as metabolically active parenchymal cells and specialized cells such as neutrophils which are often lost by conventional QC. Taken together, our work proposes a revised paradigm to quality filtering best practices-iterative QC, providing a data-driven QC framework compatible with observed biological diversity.

A monoclonal antibody targeting nonjunctional claudin-1 inhibits fibrosis in patient-derived models by modulating cell plasticity

Tissue fibrosis is a key driver of end-stage organ failure and cancer, overall accounting for up to 45% of deaths in developed countries. There is a large unmet medical need for antifibrotic therapies. Claudin-1 (CLDN1) is a member of the tight junction protein family. Although the role of CLDN1 incorporated in tight junctions is well established, the function of nonjunctional CLDN1 (njCLDN1) is largely unknown. Using highly specific monoclonal antibodies targeting a conformation-dependent epitope of exposed njCLDN1, we show in patient-derived liver three-dimensional fibrosis and human liver chimeric mouse models that CLDN1 is a mediator and target for liver fibrosis. Targeting CLDN1 reverted inflammation-induced hepatocyte profibrogenic signaling and cell fate and suppressed the myofibroblast differentiation of hepatic stellate cells. Safety studies of a fully humanized antibody in nonhuman primates did not reveal any serious adverse events even at high steady-state concentrations. Our results provide preclinical proof of concept for CLDN1-specific monoclonal antibodies for the treatment of advanced liver fibrosis and cancer prevention. Antifibrotic effects in lung and kidney fibrosis models further indicate a role of CLDN1 as a therapeutic target for tissue fibrosis across organs. In conclusion, our data pave the way for further therapeutic exploration of CLDN1-targeting therapies for fibrotic diseases in patients.

Plant Single-Cell/Nucleus RNA-seq Workflow

Single-cell transcriptomics technologies allow researchers to investigate how individual cells, in complex multicellular organisms, differentially use their common genomic DNA. In plant biology, these technologies were recently applied to reveal the transcriptomes of various plant cells isolated from different organs and different species and in response to environmental stresses. These first studies support the potential of single-cell transcriptomics technology to decipher the biological function of plant cells, their developmental programs, cell-type-specific gene networks, programs controlling plant cell response to environmental stresses, etc. In this chapter, we provide information regarding the critical steps and important information to consider when developing an experimental design in plant single-cell biology. We also describe the current status of bioinformatics tools used to analyze single-cell RNA-seq datasets and how additional emerging technologies such as spatial transcriptomics and long-read sequencing technologies will provide additional information on the differential use of the genome by plant cells.

Single cell RNA sequencing of the adult Drosophila eye reveals distinct clusters and novel marker genes for all major cell types

The adult Drosophila eye is a powerful model system for phototransduction and neurodegeneration research. However, single cell resolution transcriptomic data are lacking for this tissue. We present single cell RNA-seq data on 1-day male and female, 3-day and 7-day old male adult eyes, covering early to mature adult eyes. All major cell types, including photoreceptors, cone and pigment cells in the adult eye were captured and identified. Our data sets identified novel cell type specific marker genes, some of which were validated in vivo. R7 and R8 photoreceptors form clusters that reflect their specific Rhodopsin expression and the specific Rhodopsin expression by each R7 and R8 cluster is the major determinant to their clustering. The transcriptomic data presented in this report will facilitate a deeper mechanistic understanding of the adult fly eye as a model system.

Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material

Background

Recent technological advances opened the opportunity to simultaneously study gene expression for thousands of individual cells on a genome-wide scale. The experimental accessibility of such single-cell RNA sequencing (scRNAseq) approaches allowed gaining insights into the cell type composition of heterogeneous tissue samples of animal model systems and emerging models alike. A major prerequisite for a successful application of the method is the dissociation of complex tissues into individual cells, which often requires large amounts of input material and harsh mechanical, chemical and temperature conditions. However, the availability of tissue material may be limited for small animals, specific organs, certain developmental stages or if samples need to be acquired from collected specimens. Therefore, we evaluated different dissociation protocols to obtain single cells from small tissue samples of Drosophila melanogaster eye-antennal imaginal discs.

Results

We show that a combination of mechanical and chemical dissociation resulted in sufficient high-quality cells. As an alternative, we tested protocols for the isolation of single nuclei, which turned out to be highly efficient for fresh and frozen tissue samples. Eventually, we performed scRNAseq and single-nuclei RNA sequencing (snRNAseq) to show that the best protocols for both methods successfully identified relevant cell types. At the same time, snRNAseq resulted in less artificial gene expression that is caused by rather harsh dissociation conditions needed to obtain single cells for scRNAseq. A direct comparison of scRNAseq and snRNAseq data revealed that both datasets share biologically relevant genes among the most variable genes, and we showed differences in the relative contribution of the two approaches to identified cell types.

Conclusion

We present two dissociation protocols that allow isolating single cells and single nuclei, respectively, from low input material. Both protocols resulted in extraction of high-quality RNA for subsequent scRNAseq or snRNAseq applications. If tissue availability is limited, we recommend the snRNAseq procedure of fresh or frozen tissue samples as it is perfectly suited to obtain thorough insights into cellular diversity of complex tissue.

A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients

The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.

A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients

The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.

Advances in single-cell sequencing technology in the field of hepatocellular carcinoma

Tumors are a class of diseases characterized by altered genetic information and uncontrolled growth. Sequencing technology provide researchers with a better way to explore specific tumor pathogenesis. In recent years, single-cell sequencing technology has shone in tumor research, especially in the study of liver cancer, revealing phenomena that were unexplored by previous studies. Single-cell sequencing (SCS) is a technique for sequencing the cellular genome, transcriptome, epigenome, proteomics, or metabolomics after dissociation of tissues into single cells. Compared with traditional bulk sequencing, single-cell sequencing can dissect human tumors at single-cell resolution, finely delineate different cell types, and reveal the heterogeneity of tumor cells. In view of the diverse pathological types and complex pathogenesis of hepatocellular carcinoma (HCC), the study of the heterogeneity among tumor cells can help improve its clinical diagnosis, treatment and prognostic judgment. On this basis, SCS has revolutionized our understanding of tumor heterogeneity, tumor immune microenvironment, and clonal evolution of tumor cells. This review summarizes the basic process and development of single-cell sequencing technology and its increasing role in the field of hepatocellular carcinoma.

Opposing roles of hepatic stellate cell subpopulations in hepatocarcinogenesis

Hepatocellular carcinoma (HCC), the fourth leading cause of cancer mortality worldwide, develops almost exclusively in patients with chronic liver disease and advanced fibrosis1,2. Here we interrogated functions of hepatic stellate cells (HSCs), the main source of liver fibroblasts3, during hepatocarcinogenesis. Genetic depletion, activation or inhibition of HSCs in mouse models of HCC revealed their overall tumour-promoting role. HSCs were enriched in the preneoplastic environment, where they closely interacted with hepatocytes and modulated hepatocarcinogenesis by regulating hepatocyte proliferation and death. Analyses of mouse and human HSC subpopulations by single-cell RNA sequencing together with genetic ablation of subpopulation-enriched mediators revealed dual functions of HSCs in hepatocarcinogenesis. Hepatocyte growth factor, enriched in quiescent and cytokine-producing HSCs, protected against hepatocyte death and HCC development. By contrast, type I collagen, enriched in activated myofibroblastic HSCs, promoted proliferation and tumour development through increased stiffness and TAZ activation in pretumoural hepatocytes and through activation of discoidin domain receptor 1 in established tumours. An increased HSC imbalance between cytokine-producing HSCs and myofibroblastic HSCs during liver disease progression was associated with increased HCC risk in patients. In summary, the dynamic shift in HSC subpopulations and their mediators during chronic liver disease is associated with a switch from HCC protection to HCC promotion.

Liver zonation, revisited

The concept of hepatocyte functional zonation is well established, with differences in metabolism and xenobiotic processing determined by multiple factors including oxygen and nutrient levels across the hepatic lobule. However, recent advances in single-cell genomics technologies, including single-cell and nuclei RNA sequencing, and the rapidly evolving fields of spatial transcriptomic and proteomic profiling have greatly increased our understanding of liver zonation. Here we discuss how these transformative experimental strategies are being leveraged to dissect liver zonation at unprecedented resolution and how this new information should facilitate the emergence of novel precision medicine-based therapies for patients with liver disease.

Liver macrophages in health and disease

Single-cell and spatial transcriptomic technologies have revealed an underappreciated heterogeneity of liver macrophages. This has led us to rethink the involvement of macrophages in liver homeostasis and disease. Identification of conserved gene signatures within these cells across species and diseases is enabling the correct identification of specific macrophage subsets and the generation of more specific tools to track and study the functions of these cells. Here, we discuss what is currently known about the definitions of these different macrophage populations, the markers that can be used to identify them, how they are wired within the liver, and their functional specializations in health and disease.

Single cell transcriptomics of Atlantic salmon (Salmo salar L.) liver reveals cellular heterogeneity and immunological responses to challenge by Aeromonas salmonicida

The liver is a multitasking organ with essential functions for vertebrate health spanning metabolism and immunity. In contrast to mammals, our understanding of liver cellular heterogeneity and its role in regulating immunological status remains poorly defined in fishes. Addressing this knowledge gap, we generated a transcriptomic atlas of 47,432 nuclei isolated from the liver of Atlantic salmon (Salmo salar L.) contrasting control fish with those challenged with a pathogenic strain of Aeromonas salmonicida, a problematic bacterial pathogen in global aquaculture. We identified the major liver cell types and their sub-populations, revealing poor conservation of many hepatic cell marker genes utilized in mammals, while identifying novel heterogeneity within the hepatocyte, lymphoid, and myeloid lineages. This included polyploid hepatocytes, multiple T cell populations including γδ T cells, and candidate populations of monocytes/macrophages and dendritic cells. A dominant hepatocyte population radically remodeled its transcriptome following infection to activate the acute phase response and other defense functions, while repressing routine functions such as metabolism. These defense-specialized hepatocytes showed strong activation of genes controlling protein synthesis and secretion, presumably to support the release of acute phase proteins into circulation. The infection response further involved up-regulation of numerous genes in an immune-cell specific manner, reflecting functions in pathogen recognition and killing, antigen presentation, phagocytosis, regulation of inflammation, B cell differentiation and T cell activation. Overall, this study greatly enhances our understanding of the multifaceted role played by liver immune and non-immune cells in host defense and metabolic remodeling following infection and provides many novel cell-specific marker genes to empower future studies of this organ in fishes.

Cellular and transcriptional heterogeneity in the intrahepatic biliary epithelium

Epithelial tissues comprise heterogeneous cellular subpopulations, which often compartmentalize specialized functions like absorption and secretion to distinct cell types. In the liver, hepatocytes and biliary epithelial cells (BECs; also called cholangiocytes) are the two major epithelial lineages and play distinct roles in (1) metabolism, protein synthesis, detoxification, and (2) bile transport and modification, respectively. Recent technological advances, including single cell transcriptomic assays, have shed new light on well-established heterogeneity among hepatocytes, endothelial cells, and immune cells in the liver. However, a "ground truth" understanding of molecular heterogeneity in BECs has remained elusive, and the field currently lacks a set of consensus biomarkers for identifying BEC subpopulations. Here, we review long-standing definitions of BEC heterogeneity as well as emerging studies that aim to characterize BEC subpopulations using next generation single cell assays. Understanding cellular heterogeneity in the intrahepatic bile ducts holds promise for expanding our foundational mechanistic knowledge of BECs during homeostasis and disease.

Macrophage functional diversity in NAFLD - more than inflammation

Macrophages have diverse phenotypes and functions due to differences in their origin, location and pathophysiological context. Although their main role in the liver has been described as immunoregulatory and detoxifying, changes in macrophage phenotypes, diversity, dynamics and function have been reported during obesity-related complications such as non-alcoholic fatty liver disease (NAFLD). NAFLD encompasses multiple disease states from hepatic steatosis to non-alcoholic steatohepatitis (NASH), fibrosis, cirrhosis and hepatocarcinoma. Obesity and insulin resistance are prominent risk factors for NASH, a disease with a high worldwide prevalence and no approved treatment. In this Review, we discuss the turnover and function of liver-resident macrophages (Kupffer cells) and monocyte-derived hepatic macrophages. We examine these populations in both steady state and during NAFLD, with an emphasis on NASH. The explosion in high-throughput gene expression analysis using single-cell RNA sequencing (scRNA-seq) within the last 5 years has revolutionized the study of macrophage heterogeneity, substantially increasing our understanding of the composition and diversity of tissue macrophages, including in the liver. Here, we highlight scRNA-seq findings from the last 5 years on the diversity of liver macrophages in homeostasis and metabolic disease, and reveal hepatic macrophage function beyond their classically described inflammatory role in the progression of NAFLD and NASH pathogenesis.

Unraveling the Complexity of Liver Disease One Cell at a Time

The human liver is a complex organ made up of multiple specialized cell types that carry out key physiological functions. An incomplete understanding of liver biology limits our ability to develop therapeutics to prevent chronic liver diseases, liver cancers, and death as a result of organ failure. Recently, single-cell modalities have expanded our understanding of the cellular phenotypic heterogeneity and intercellular cross-talk in liver health and disease. This review summarizes these findings and looks forward to highlighting new avenues for the application of single-cell genomics to unravel unknown pathogenic pathways and disease mechanisms for the development of new therapeutics targeting liver pathology. As these technologies mature, their integration into clinical data analysis will aid in patient stratification and in developing treatment plans for patients suffering from liver disease.

Intravital Imaging of Inflammatory Response in Liver Disease

The healthy liver requires a strictly controlled crosstalk between immune and nonimmune cells to maintain its function and homeostasis. A well-conditioned immune system can effectively recognize and clear noxious stimuli by a self-limited, small-scale inflammatory response. This regulated inflammatory process enables the liver to cope with daily microbial exposure and metabolic stress, which is beneficial for hepatic self-renewal and tissue remodeling. However, the failure to clear noxious stimuli or dysregulation of immune response can lead to uncontrolled liver inflammation, liver dysfunction, and severe liver disease. Numerous highly dynamic circulating immune cells and sessile resident immune and parenchymal cells interact and communicate with each other in an incredibly complex way to regulate the inflammatory response in both healthy and diseased liver. Intravital imaging is a powerful tool to visualize individual cells in vivo and has been widely used for dissecting the behavior and interactions between various cell types in the complex architecture of the liver. Here, we summarize some new findings obtained with the use of intravital imaging, which enhances our understanding of the complexity of immune cell behavior, cell–cell interaction, and spatial organization during the physiological and pathological liver inflammatory response.

Spatial transcriptomics identifies enriched gene expression and cell types in human liver fibrosis

Liver fibrosis and cirrhosis have limited therapeutic options and represent a serious unmet patient need. Recent use of single‐cell RNA sequencing (scRNAseq) has identified enriched cell types infiltrating cirrhotic livers but without defining the microanatomical location of these lineages thoroughly. To assess whether fibrotic liver regions specifically harbor enriched cell types, we explored whether whole‐tissue spatial transcriptomics combined with scRNAseq and gene deconvolution analysis could be used to localize cell types in cirrhotic explants of patients with end‐stage liver disease (total n = 8; primary sclerosing cholangitis, n = 4; primary biliary cholangitis, n = 2, alcohol‐related liver disease, n = 2). Spatial transcriptomics clearly identified tissue areas of distinct gene expression that strongly correlated with the total area (Spearman r = 0.97, p = 0.0004) and precise location (parenchyma, 87.9% mean congruency; range, 73.1%–97.1%; fibrosis, 68.5% mean congruency; range, 41.0%–91.7%) of liver regions classified as parenchymal or fibrotic by conventional histology. Deconvolution and enumeration of parenchymal and fibrotic gene content as measured by spatial transcriptomics into distinct cell states revealed significantly higher frequencies of ACTA2+ FABP4+ and COL3A1+ mesenchymal cells, IL17RA+ S100A8+ and FCER1G+ tissue monocytes, VCAM1+ SDC3+ Kupffer cells, CCL4+ CCL5+ KLRB1+ and GZMA+ IL17RA+ T cells and HLA‐DR+, CD37+ CXCR4+ and IGHM+ IGHG+ B cells in fibrotic liver regions compared with parenchymal areas of cirrhotic explants. Conclusion: Our findings indicate that spatial transcriptomes of parenchymal and fibrotic liver regions express unique gene content within cirrhotic liver and demonstrate proof of concept that spatial transcriptomes combined with additional RNA sequencing methodologies can refine the localization of gene content and cell lineages in the search for antifibrotic targets.

Single-Cell Transcriptomics of Liver Cancer: Hype or Insights?

Hepatocellular carcinoma (HCC) is characterized by its high degrees of both inter- and intratumoral heterogeneity. Its complex tumor microenvironment is also crucial in promoting tumor progression. Recent advances in single-cell RNA sequencing provide an important highway to characterize the underlying pathogenesis and heterogeneity of HCC in an unprecedented degree of resolution. This review discusses the up-to-date discoveries from the latest studies of HCC with respect to the strength of single-cell RNA sequencing. We discuss its use in the dissection of the landscape of the intricate HCC ecosystem and highlight the major features at cellular levels, including the malignant cells, different immune cell types, and the various cell-cell interactions, which are crucial for developing effective immunotherapies. Finally, its translational applications will be discussed. Altogether, these explorations may give us some hints at the tumor growth and progression and drug resistance and recurrence, particularly in this era of personalized medicine.

Ceramides and Acute Kidney Injury

Altered lipid metabolism is a characteristic feature and potential driving factor of acute kidney injury (AKI). Of the lipids that accumulate in injured renal tissues, ceramides are potent regulators of metabolism and cell fate. Up-regulation of ceramide synthesis is a common feature shared across several AKI etiologies in vitro and in vivo. Furthermore, ceramide accumulation is an early event in the natural history of AKI that precedes cell death and organ dysfunction. Emerging evidence suggests that inhibition of ceramide accumulation may improve renal outcomes in several models of AKI. This review examines the landscape of ceramide metabolism and regulation in the healthy and injured kidney. Furthermore, we discuss the body of literature regarding ceramides as therapeutic targets for AKI and consider potential mechanisms by which ceramides drive kidney pathogenesis.

Hepatic stellate cells in physiology and pathology

Hepatic stellate cells (HSCs) comprise a minor cell population in the liver but serve numerous critical functions in the normal liver and in response to injury. HSCs are primarily known for their activation upon liver injury and for producing the collagen-rich extracellular matrix in liver fibrosis. In the absence of liver injury, HSCs reside in a quiescent state, in which their main function appears to be the storage of retinoids or vitamin A-containing metabolites. Less appreciated functions of HSCs include amplifying the hepatic inflammatory response and expressing growth factors that are critical for liver development and both the initiation and termination of liver regeneration. Recent single-cell RNA sequencing studies have corroborated earlier studies indictaing that HSC activation involves a diverse array of phenotypic alterations and identified unique HSC populations. This review serves to highlight these many functions of HSCs, and to briefly describe the recent genetic tools that will help to thoroughly investigate the role of HSCs in hepatic physiology and pathology.

Characterization of transcript enrichment and detection bias in single-nucleus RNA-seq for mapping of distinct human adipocyte lineages

Single-cell RNA sequencing (scRNA-seq) enables molecular characterization of complex biological tissues at high resolution. The requirement of single-cell extraction, however, makes it challenging for profiling tissues such as adipose tissue, for which collection of intact single adipocytes is complicated by their fragile nature. For such tissues, single-nucleus extraction is often much more efficient and therefore single-nucleus RNA sequencing (snRNA-seq) presents an alternative to scRNA-seq. However, nuclear transcripts represent only a fraction of the transcriptome in a single cell, with snRNA-seq marked with inherent transcript enrichment and detection biases. Therefore, snRNA-seq may be inadequate for mapping important transcriptional signatures in adipose tissue. In this study, we compare the transcriptomic landscape of single nuclei isolated from preadipocytes and mature adipocytes across human white and brown adipocyte lineages, with whole-cell transcriptome. We show that snRNA-seq is capable of identifying the broad cell types present in scRNA-seq at all states of adipogenesis. However, we also explore how and why the nuclear transcriptome is biased and limited, as well as how it can be advantageous. We robustly characterize the enrichment of nuclear-localized transcripts and adipogenic regulatory lncRNAs in snRNA-seq, while also providing a detailed understanding for the preferential detection of long genes upon using this technique. To remove such technical detection biases, we propose a normalization strategy for a more accurate comparison of nuclear and cellular data. Finally, we show successful integration of scRNA-seq and snRNA-seq data sets with existing bioinformatic tools. Overall, our results illustrate the applicability of snRNA-seq for the characterization of cellular diversity in the adipose tissue.