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

Single-cell technologies in psoriasis

Psoriasis is a chronic and recurrent inflammatory skin disorder. The primary manifestation of psoriasis arises from disturbances in the cutaneous immune microenvironment, but the specific functions of the cellular components within this microenvironment remain unknown. Recent advancements in single-cell technologies have enabled the detection of multi-omics at the level of individual cells, including single-cell transcriptome, proteome, and metabolome, which have been successfully applied in studying autoimmune diseases, and other pathologies. These techniques allow the identification of heterogeneous cell clusters and their varying contributions to disease development. Considering the immunological traits of psoriasis, an in-depth exploration of immune cells and their interactions with cutaneous parenchymal cells can markedly advance our comprehension of the mechanisms underlying the onset and recurrence of psoriasis. In this comprehensive review, we present an overview of recent applications of single-cell technologies in psoriasis, aiming to improve our understanding of the underlying mechanisms of this disorder.

Noninvasive assessment of organ-specific and shared pathways in multi-organ fibrosis using T1 mapping

Fibrotic diseases affect multiple organs and are associated with morbidity and mortality. To examine organ-specific and shared biologic mechanisms that underlie fibrosis in different organs, we developed machine learning models to quantify T1 time, a marker of interstitial fibrosis, in the liver, pancreas, heart and kidney among 43,881 UK Biobank participants who underwent magnetic resonance imaging. In phenome-wide association analyses, we demonstrate the association of increased organ-specific T1 time, reflecting increased interstitial fibrosis, with prevalent diseases across multiple organ systems. In genome-wide association analyses, we identified 27, 18, 11 and 10 independent genetic loci associated with liver, pancreas, myocardial and renal cortex T1 time, respectively. There was a modest genetic correlation between the examined organs. Several loci overlapped across the examined organs implicating genes involved in a myriad of biologic pathways including metal ion transport (SLC39A8, HFE and TMPRSS6), glucose metabolism (PCK2), blood group antigens (ABO and FUT2), immune function (BANK1 and PPP3CA), inflammation (NFKB1) and mitosis (CENPE). Finally, we found that an increasing number of organs with T1 time falling in the top quintile was associated with increased mortality in the population. Individuals with a high burden of fibrosis in ≥3 organs had a 3-fold increase in mortality compared to those with a low burden of fibrosis across all examined organs in multivariable-adjusted analysis (hazard ratio = 3.31, 95% confidence interval 1.77-6.19; P = 1.78 × 10-4). By leveraging machine learning to quantify T1 time across multiple organs at scale, we uncovered new organ-specific and shared biologic pathways underlying fibrosis that may provide therapeutic targets.

Acquisition of epithelial plasticity in human chronic liver disease

For many adult human organs, tissue regeneration during chronic disease remains a controversial subject. Regenerative processes are easily observed in animal models, and their underlying mechanisms are becoming well characterized1-4, but technical challenges and ethical aspects are limiting the validation of these results in humans. We decided to address this difficulty with respect to the liver. This organ displays the remarkable ability to regenerate after acute injury, although liver regeneration in the context of recurring injury remains to be fully demonstrated. Here we performed single-nucleus RNA sequencing (snRNA-seq) on 47 liver biopsies from patients with different stages of metabolic dysfunction-associated steatotic liver disease to establish a cellular map of the liver during disease progression. We then combined these single-cell-level data with advanced 3D imaging to reveal profound changes in the liver architecture. Hepatocytes lose their zonation and considerable reorganization of the biliary tree takes place. More importantly, our study uncovers transdifferentiation events that occur between hepatocytes and cholangiocytes without the presence of adult stem cells or developmental progenitor activation. Detailed analyses and functional validations using cholangiocyte organoids confirm the importance of the PI3K-AKT-mTOR pathway in this process, thereby connecting this acquisition of plasticity to insulin signalling. Together, our data indicate that chronic injury creates an environment that induces cellular plasticity in human organs, and understanding the underlying mechanisms of this process could open new therapeutic avenues in the management of chronic diseases.

Advances in long-read single-cell transcriptomics

Long-read single-cell transcriptomics (scRNA-Seq) is revolutionizing the way we profile heterogeneity in disease. Traditional short-read scRNA-Seq methods are limited in their ability to provide complete transcript coverage, resolve isoforms, and identify novel transcripts. The scRNA-Seq protocols developed for long-read sequencing platforms overcome these limitations by enabling the characterization of full-length transcripts. Long-read scRNA-Seq techniques initially suffered from comparatively poor accuracy compared to short read scRNA-Seq. However, with improvements in accuracy, accessibility, and cost efficiency, long-reads are gaining popularity in the field of scRNA-Seq. This review details the advances in long-read scRNA-Seq, with an emphasis on library preparation protocols and downstream bioinformatics analysis tools.

Deconvolution analysis identified altered hepatic cell landscape in primary sclerosing cholangitis and primary biliary cholangitis

Introduction

Primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC) are characterized by ductular reaction, hepatic inflammation, and liver fibrosis. Hepatic cells are heterogeneous, and functional roles of different hepatic cell phenotypes are still not defined in the pathophysiology of cholangiopathies. Cell deconvolution analysis estimates cell fractions of different cell phenotypes in bulk transcriptome data, and CIBERSORTx is a powerful deconvolution method to estimate cell composition in microarray data. CIBERSORTx performs estimation based on the reference file, which is referred to as signature matrix, and allows users to create custom signature matrix to identify specific phenotypes. In the current study, we created two custom signature matrices using two single cell RNA sequencing data of hepatic cells and performed deconvolution for bulk microarray data of liver tissues including PSC and PBC patients.

Methods

Custom signature matrix files were created using single-cell RNA sequencing data downloaded from GSE185477 and GSE115469. Custom signature matrices were validated for their deconvolution performance using validation data sets. Cell composition of each hepatic cell phenotype in the liver, which was identified in custom signature matrices, was calculated by CIBERSORTx and bulk RNA sequencing data of GSE159676. Deconvolution results were validated by analyzing marker expression for the cell phenotype in GSE159676 data.

Results

CIBERSORTx and custom signature matrices showed comprehensive performance in estimation of population of various hepatic cell phenotypes. We identified increased population of large cholangiocytes in PSC and PBC livers, which is in agreement with previous studies referred to as ductular reaction, supporting the effectiveness and reliability of deconvolution analysis in this study. Interestingly, we identified decreased population of small cholangiocytes, periportal hepatocytes, and interzonal hepatocytes in PSC and PBC liver tissues compared to healthy livers.

Discussion

Although further studies are required to elucidate the roles of these hepatic cell phenotypes in cholestatic liver injury, our approach provides important implications that cell functions may differ depending on phenotypes, even in the same cell type during liver injury. Deconvolution analysis using CIBERSORTx could provide a novel approach for studies of specific hepatic cell phenotypes in liver diseases.

Perturbed liver gene zonation in a mouse model of non-alcoholic steatohepatitis

Liver zonation characterizes the separation of metabolic pathways along the lobules and is required for optimal hepatic function. Wnt signaling is a master regulator of spatial liver zonation. A perivenous-periportal Wnt activity gradient orchestrates metabolic zonation by activating gene expression in perivenous hepatocytes, while suppressing gene expression in their periportal counterparts. However, the understanding as to the liver gene zonation and zonation regulators in diseases is limited. Non-alcoholic steatohepatitis (NASH) is a chronic liver disease characterized by fat accumulation, inflammation, and fibrosis. Here, we investigated the perturbation of liver gene zonation in a mouse NASH model by combining spatial transcriptomics, bulk RNAseq and in situ hybridization. Wnt-target genes represented a major subset of genes showing altered spatial expression in the NASH liver. The altered Wnt-target gene expression levels and zonation spatial patterns were in line with the up regulation of Wnt regulators and the augmentation of Wnt signaling. Particularly, we found that the Wnt activator Rspo3 expression was restricted to the perivenous zone in control liver but expanded to the periportal zone in NASH liver. AAV8-mediated RSPO3 overexpression in controls resulted in zonation changes, and further amplified the disturbed zonation of Wnt-target genes in NASH, similarly Rspo3 knockdown in Rspo3+/- mice resulted in zonation changes of Wnt-target genes in both chow and HFD mouse. Interestingly, there were no impacts on steatosis, inflammation, or fibrosis NASH pathology from RSPO3 overexpression nor Rspo3 knockdown. In summary, our study demonstrated the alteration of Wnt signaling in a mouse NASH model, leading to perturbed liver zonation.

A spatiotemporal atlas of cholestatic injury and repair in mice

Cholestatic liver injuries, characterized by regional damage around the bile ductular region, lack curative therapies and cause considerable mortality. Here we generated a high-definition spatiotemporal atlas of gene expression during cholestatic injury and repair in mice by integrating spatial enhanced resolution omics sequencing and single-cell transcriptomics. Spatiotemporal analyses revealed a key role of cholangiocyte-driven signaling correlating with the periportal damage-repair response. Cholangiocytes express genes related to recruitment and differentiation of lipid-associated macrophages, which generate feedback signals enhancing ductular reaction. Moreover, cholangiocytes express high TGFβ in association with the conversion of liver progenitor-like cells into cholangiocytes during injury and the dampened proliferation of periportal hepatocytes during recovery. Notably, Atoh8 restricts hepatocyte proliferation during 3,5-diethoxycarbonyl-1,4-dihydro-collidin damage and is quickly downregulated after injury withdrawal, allowing hepatocytes to respond to growth signals. Our findings lay a keystone for in-depth studies of cellular dynamics and molecular mechanisms of cholestatic injuries, which may further develop into therapies for cholangiopathies.

Single-cell and single-nucleus RNA-sequencing from paired normal-adenocarcinoma lung samples provide both common and discordant biological insights

Whether single-cell RNA-sequencing (scRNA-seq) captures the same biological information as single-nucleus RNA-sequencing (snRNA-seq) remains uncertain and likely to be context-dependent. Herein, a head-to-head comparison was performed in matched normal-adenocarcinoma human lung samples to assess biological insights derived from scRNA-seq versus snRNA-seq and better understand the cellular transition that occurs from normal to tumoral tissue. Here, the transcriptome of 160,621 cells/nuclei was obtained. In non-tumor lung, cell type proportions varied widely between scRNA-seq and snRNA-seq with a predominance of immune cells in the former (81.5%) and epithelial cells (69.9%) in the later. Similar results were observed in adenocarcinomas, in addition to an overall increase in cell type heterogeneity and a greater prevalence of copy number variants in cells of epithelial origin, which suggests malignant assignment. The cell type transition that occurs from normal lung tissue to adenocarcinoma was not always concordant whether cells or nuclei were examined. As expected, large differential expression of the whole-cell and nuclear transcriptome was observed, but cell-type specific changes of paired normal and tumor lung samples revealed a set of common genes in the cells and nuclei involved in cancer-related pathways. In addition, we showed that the ligand-receptor interactome landscape of lung adenocarcinoma was largely different whether cells or nuclei were evaluated. Immune cell depletion in fresh specimens partly mitigated the difference in cell type composition observed between cells and nuclei. However, the extra manipulations affected cell viability and amplified the transcriptional signatures associated with stress responses. In conclusion, research applications focussing on mapping the immune landscape of lung adenocarcinoma benefit from scRNA-seq in fresh samples, whereas snRNA-seq of frozen samples provide a low-cost alternative to profile more epithelial and cancer cells, and yield cell type proportions that more closely match tissue content.

Single-cell, single-nucleus, and spatial transcriptomics characterization of the immunological landscape in the healthy and PSC human liver

BACKGROUND & AIMS

Primary sclerosing cholangitis (PSC) is an immune-mediated cholestatic liver disease for which there is an unmet need to understand the cellular composition of the affected liver and how it underlies disease pathogenesis. We aimed to generate a comprehensive atlas of the PSC liver using multi-omic modalities and protein-based functional validation.

METHODS

We employed single-cell and single-nucleus RNA sequencing (47,156 cells and 23,000 nuclei) and spatial transcriptomics (one sample by 10x Visium and five samples with Nanostring GeoMx DSP) to profile the cellular ecosystem in 10 PSC livers. Transcriptomic profiles were compared to 24 neurologically deceased donor livers (107,542 cells) and spatial transcriptomics controls, as well as 18,240 cells and 20,202 nuclei from three PBC livers. Flow cytometry was performed to validate PSC-specific differences in immune cell phenotype and function.

RESULTS

PSC explants with parenchymal cirrhosis and prominent periductal fibrosis contained a population of cholangiocyte-like hepatocytes that were surrounded by diverse immune cell populations. PSC-associated biliary, mesenchymal, and endothelial populations expressed chemokine and cytokine transcripts involved in immune cell recruitment. Additionally, expanded CD4+ T cells and recruited myeloid populations in the PSC liver expressed the corresponding receptors to these chemokines and cytokines, suggesting potential recruitment. Tissue-resident macrophages, by contrast, were reduced in number and exhibited a dysfunctional and downregulated inflammatory response to lipopolysaccharide and interferon-γ stimulation.

CONCLUSIONS

We present a comprehensive atlas of the PSC liver and demonstrate an exhaustion-like phenotype of myeloid cells and markers of chronic cytokine expression in late-stage PSC lesions. This atlas expands our understanding of the cellular complexity of PSC and has potential to guide the development of novel treatments.

IMPACT AND IMPLICATIONS

Primary sclerosing cholangitis (PSC) is a rare liver disease characterized by chronic inflammation and irreparable damage to the bile ducts, which eventually results in liver failure. Due to a limited understanding of the underlying pathogenesis of disease, treatment options are limited. To address this, we sequenced healthy and diseased livers to compare the activity, interactions, and localization of immune and non-immune cells. This revealed that hepatocytes lining PSC scar regions co-express cholangiocyte markers, whereas immune cells infiltrate the scar lesions. Of these cells, macrophages, which typically contribute to tissue repair, were enriched in immunoregulatory genes and demonstrated a lack of responsiveness to stimulation. These cells may be involved in maintaining hepatic inflammation and could be a target for novel therapies.

Plasticity, heterogeneity, and multifunctionality of hepatic stellate cells in liver pathophysiology

HSCs, the resident pericytes of the liver, have consistently been at the forefront of liver research due to their crucial roles in various hepatic pathological processes. Prior literature often depicted HSCs in a binary framework, categorizing them as either quiescent or activated. However, recent advances in HSC research, particularly the advent of single-cell RNA-sequencing, have revolutionized our understanding of these cells. This sophisticated technique offers an unparalleled, high-resolution insight into HSC populations, uncovering a spectrum of diversity and functional heterogeneity across various physiological states of the liver, ranging from liver development to the liver aging process. The single-cell RNA-sequencing revelations have also highlighted the intrinsic plasticity of HSCs and underscored their complex roles in a myriad of pathophysiological processes, including liver injury, repair, and carcinogenesis. This review aims to integrate and clarify these recent discoveries, focusing on how the inherent plasticity of HSCs is central to their dynamic roles both in maintaining liver homeostasis and orchestrating responses to liver injury. Future research will clarify whether findings from rodent models can be translated to human livers and guide how these insights are harnessed to develop targeted therapeutic interventions.

Emerging Roles of Spatial Transcriptomics in Liver Research

Spatial transcriptomics, leveraging sequencing- and imaging-based techniques, has emerged as a groundbreaking technology for mapping gene expression within the complex architectures of tissues. This approach provides an in-depth understanding of cellular and molecular dynamics across various states of healthy and diseased livers. Through the integration of sophisticated bioinformatics strategies, it enables detailed exploration of cellular heterogeneity, transitions in cell states, and intricate cell-cell interactions with remarkable precision. In liver research, spatial transcriptomics has been particularly revelatory, identifying distinct zonated functions of hepatocytes that are crucial for understanding the metabolic and detoxification processes of the liver. Moreover, this technology has unveiled new insights into the pathogenesis of liver diseases, such as the role of lipid-associated macrophages in steatosis and endothelial cell signals in liver regeneration and repair. In the domain of liver cancer, spatial transcriptomics has proven instrumental in delineating intratumor heterogeneity, identifying supportive microenvironmental niches and revealing the complex interplay between tumor cells and the immune system as well as susceptibility to immune checkpoint inhibitors. In conclusion, spatial transcriptomics represents a significant advance in hepatology, promising to enhance our understanding and treatment of liver diseases.

Spatial genomics: mapping human steatotic liver disease

Metabolic dysfunction-associated steatotic liver disease (MASLD, formerly known as non-alcoholic fatty liver disease) is a leading cause of chronic liver disease worldwide. MASLD can progress to metabolic dysfunction-associated steatohepatitis (MASH, formerly known as non-alcoholic steatohepatitis) with subsequent liver cirrhosis and hepatocellular carcinoma formation. The advent of current technologies such as single-cell and single-nuclei RNA sequencing have transformed our understanding of the liver in homeostasis and disease. The next frontier is contextualizing this single-cell information in its native spatial orientation. This understanding will markedly accelerate discovery science in hepatology, resulting in a further step-change in our knowledge of liver biology and pathobiology. In this Review, we discuss up-to-date knowledge of MASLD development and progression and how the burgeoning field of spatial genomics is driving exciting new developments in our understanding of human liver disease pathogenesis and therapeutic target identification.

scGREAT: Transformer-based deep-language model for gene regulatory network inference from single-cell transcriptomics

Gene regulatory networks (GRNs) involve complex and multi-layer regulatory interactions between regulators and their target genes. Precise knowledge of GRNs is important in understanding cellular processes and molecular functions. Recent breakthroughs in single-cell sequencing technology made it possible to infer GRNs at single-cell level. Existing methods, however, are limited by expensive computations, and sometimes simplistic assumptions. To overcome these obstacles, we propose scGREAT, a framework to infer GRN using gene embeddings and transformer from single-cell transcriptomics. scGREAT starts by constructing gene expression and gene biotext dictionaries from scRNA-seq data and gene text information. The representation of TF gene pairs is learned through optimizing embedding space by transformer-based engine. Results illustrated scGREAT outperformed other contemporary methods on benchmarks. Besides, gene representations from scGREAT provide valuable gene regulation insights, and external validation on spatial transcriptomics illuminated the mechanism behind scGREAT annotation. Moreover, scGREAT identified several TF target regulations corroborated in studies.

Deciphering the cellular heterogeneity of the insect brain with single-cell RNA sequencing

Insects show highly complicated adaptive and sophisticated behaviors, including spatial orientation skills, learning ability, and social interaction. These behaviors are controlled by the insect brain, the central part of the nervous system. The tiny insect brain consists of millions of highly differentiated and interconnected cells forming a complex network. Decades of research has gone into an understanding of which parts of the insect brain possess particular behaviors, but exactly how they modulate these functional consequences needs to be clarified. Detailed description of the brain and behavior is required to decipher the complexity of cell types, as well as their connectivity and function. Single-cell RNA-sequencing (scRNA-seq) has emerged recently as a breakthrough technology to understand the transcriptome at cellular resolution. With scRNA-seq, it is possible to uncover the cellular heterogeneity of brain cells and elucidate their specific functions and state. In this review, we first review the basic structure of insect brains and the links to insect behaviors mainly focusing on learning and memory. Then the scRNA applications on insect brains are introduced by representative studies. Single-cell RNA-seq has allowed researchers to classify cell subpopulations within different insect brain regions, pinpoint single-cell developmental trajectories, and identify gene regulatory networks. These developments empower the advances in neuroscience and shed light on the intricate problems in understanding insect brain functions and behaviors.

ICARUS v3, a massively scalable web server for single-cell RNA-seq analysis of millions of cells

MOTIVATION

In recent years, improvements in throughput of single-cell RNA-seq have resulted in a significant increase in the number of cells profiled. The generation of single-cell RNA-seq datasets comprising >1 million cells is becoming increasingly common, giving rise to demands for more efficient computational workflows.

RESULTS

We present an update to our single-cell RNA-seq analysis web server application, ICARUS (available at https://launch.icarus-scrnaseq.cloud.edu.au) that allows effective analysis of large-scale single-cell RNA-seq datasets. ICARUS v3 utilizes the geometric cell sketching method to subsample cells from the overall dataset for dimensionality reduction and clustering that can be then projected to the large dataset. We then extend this functionality to select a representative subset of cells for downstream data analysis applications including differential expression analysis, gene co-expression network construction, gene regulatory network construction, trajectory analysis, cell-cell communication inference, and cell cluster associations to GWAS traits. We demonstrate analysis of single-cell RNA-seq datasets using ICARUS v3 of 1.3 million cells completed within the hour.

AVAILABILITY AND IMPLEMENTATION

ICARUS is available at https://launch.icarus-scrnaseq.cloud.edu.au.

Mapping the cellular landscape of Atlantic salmon head kidney by single cell and single nucleus transcriptomics

Single-cell transcriptomics is the current gold standard for global gene expression profiling, not only in mammals and model species, but also in non-model fish species. This is a rapidly expanding field, creating a deeper understanding of tissue heterogeneity and the distinct functions of individual cells, making it possible to explore the complexities of immunology and gene expression on a highly resolved level. In this study, we compared two single cell transcriptomic approaches to investigate cellular heterogeneity within the head kidney of healthy farmed Atlantic salmon (Salmo salar). We compared 14,149 cell transcriptomes assayed by single cell RNA-seq (scRNA-seq) with 18,067 nuclei transcriptomes captured by single nucleus RNA-Seq (snRNA-seq). Both approaches detected eight major cell populations in common: granulocytes, heamatopoietic stem cells, erythrocytes, mononuclear phagocytes, thrombocytes, B cells, NK-like cells, and T cells. Four additional cell types, endothelial, epithelial, interrenal, and mesenchymal cells, were detected in the snRNA-seq dataset, but appeared to be lost during preparation of the single cell suspension submitted for scRNA-seq library generation. We identified additional heterogeneity and subpopulations within the B cells, T cells, and endothelial cells, and revealed developmental trajectories of heamatopoietic stem cells into differentiated granulocyte and mononuclear phagocyte populations. Gene expression profiles of B cell subtypes revealed distinct IgM and IgT-skewed resting B cell lineages and provided insights into the regulation of B cell lymphopoiesis. The analysis revealed eleven T cell sub-populations, displaying a level of T cell heterogeneity in salmon head kidney comparable to that observed in mammals, including distinct subsets of cd4/cd8-negative T cells, such as tcrγ positive, progenitor-like, and cytotoxic cells. Although snRNA-seq and scRNA-seq were both useful to resolve cell type-specific expression in the Atlantic salmon head kidney, the snRNA-seq pipeline was overall more robust in identifying several cell types and subpopulations. While scRNA-seq displayed higher levels of ribosomal and mitochondrial genes, snRNA-seq captured more transcription factor genes. However, only scRNA-seq-generated data was useful for cell trajectory inference within the myeloid lineage. In conclusion, this study systematically outlines the relative merits of scRNA-seq and snRNA-seq in Atlantic salmon, enhances understanding of teleost immune cell lineages, and provides a comprehensive list of markers for identifying major cell populations in the head kidney with significant immune relevance.

Technical optimization of spatially resolved single-cell transcriptomic datasets to study clinical liver disease

Single cell and spatially resolved 'omic' techniques have enabled deep characterization of clinical pathologies that remain poorly understood, providing unprecedented insights into molecular mechanisms of disease. However, transcriptomic platforms are costly, limiting sample size, which increases the possibility of pre-analytical variables such as tissue processing and storage procedures impacting RNA quality and downstream analyses. Furthermore, spatial transcriptomics have not yet reached single cell resolution, leading to the development of multiple deconvolution methods to predict individual cell types within each transcriptome 'spot' on tissue sections. In this study, we performed spatial transcriptomics and single nucleus RNA sequencing (snRNAseq) on matched specimens from patients with either histologically normal or advanced fibrosis to establish important aspects of tissue handling, data processing, and downstream analyses of biobanked liver samples. We observed that tissue preservation technique impacts transcriptomic data, especially in fibrotic liver. Single cell mapping of the spatial transcriptome using paired snRNAseq data generated a spatially resolved, single cell dataset with 24 unique liver cell phenotypes. We determined that cell-cell interactions predicted using ligand-receptor analysis of snRNAseq data poorly correlated with cellular relationships identified using spatial transcriptomics. Our study provides a framework for generating spatially resolved, single cell datasets to study gene expression and cell-cell interactions in biobanked clinical samples with advanced liver disease.

Comparison of the single-cell and single-nucleus hepatic myeloid landscape within decompensated cirrhosis patients

Background and aims

A complete understanding of disease pathophysiology in advanced liver disease is hampered by the challenges posed by clinical specimen collection. Notably, in these patients, a transjugular liver biopsy (TJB) is the only safe way to obtain liver tissue. However, it remains unclear whether successful sequencing of this extremely small and fragile tissue can be achieved for downstream characterization of the hepatic landscape.

Methods

Here we leveraged in-house available single-cell RNA-sequencing (scRNA-seq) and single-nucleus (snRNA-seq) technologies and accompanying tissue processing protocols and performed an in-patient comparison on TJB's from decompensated cirrhosis patients (n = 3).

Results

We confirmed a high concordance between nuclear and whole cell transcriptomes and captured 31,410 single nuclei and 6,152 single cells, respectively. The two platforms revealed similar diversity since all 8 major cell types could be identified, albeit with different cellular proportions thereof. Most importantly, hepatocytes were most abundant in snRNA-seq, while lymphocyte frequencies were elevated in scRNA-seq. We next focused our attention on hepatic myeloid cells due to their key role in injury and repair during chronic liver disease. Comparison of their transcriptional signatures indicated that these were largely overlapping between the two platforms. However, the scRNA-seq platform failed to recover sufficient Kupffer cell numbers, and other monocytes/macrophages featured elevated expression of stress-related parameters.

Conclusion

Our results indicate that single-nucleus transcriptome sequencing provides an effective means to overcome complications associated with clinical specimen collection and could sufficiently profile all major hepatic cell types including all myeloid cell subsets.

C-C chemokine receptor type 7 (CCR7) regulates hepatic CD8 + T cell homeostasis and response to acute liver injury

BACKGROUND AND AIMS

Acute liver failure (ALF) is a rare but life-threatening condition, and DILI, particularly acetaminophen toxicity, is the leading cause of ALF. Innate immune mechanisms further perpetuate liver injury, while the role of the adaptive immune system in DILI-related ALF is unclear.

APPROACH AND RESULTS

We analyzed liver tissue from 2 independent patient cohorts with ALF and identified hepatic T cell infiltration as a prominent feature in human ALF. CD8 + T cells were characterized by zonation toward necrotic regions and an activated gene expression signature. In murine acetaminophen-induced liver injury, intravital microscopy revealed zonation of CD8 + but not CD4 + T cells at necrotic areas. Gene expression analysis exposed upregulated C-C chemokine receptor 7 (CCR7) and its ligand CCL21 in the liver as well as a broadly activated phenotype of hepatic CD8 + T cells. In 2 mouse models of ALF, Ccr7-/- mice had significantly aggravated early-phase liver damage. Functionally, CCR7 was not involved in the recruitment of CD8 + T cells, but regulated their activation profile potentially through egress to lymphatics. Ccr7-/- CD8 + T cells were characterized by elevated expression of activation, effector, and exhaustion profiles. Adoptive transfer revealed preferential homing of CCR7-deficient CD8 + T cells to the liver, and depletion of CD8 + T cells attenuated liver damage in mice.

CONCLUSIONS

Our study demonstrates the involvement of the adaptive immune system in ALF in humans and mice. We identify the CCR7-CCL21 axis as an important regulatory pathway, providing downstream protection against T cell-mediated liver injury.

"The Good, the Bad, and the Ugly" - About Diverse Phenotypes of Hepatic Stellate Cells in the Liver

Hepatic stellate cells (HSCs) and their activated derivatives, often referred to as myofibroblasts (MFs), play a key role in progression of chronic liver injuries leading to fibrosis, cirrhosis, and hepatocellular carcinoma. Until recently, MFs were considered a homogenous cell type majorly due to lack of techniques that allow complex molecular studies at a single-cell resolution. Recent technical advancements in genetic lineage-tracing models as well as the exponential growth of studies with single-cell transcriptome and proteome analyses have uncovered hidden heterogeneities among the HSC and MF populations in healthy states as well as chronic liver injuries at the various stages of tissue deformation. The identification of different phenotypes along the HSC/MF axis, which either maintain essential liver functions ("good" HSCs), emerge during fibrosis ("bad" HSCs), or even promote hepatocellular carcinoma ("ugly" HSCs), may lay the foundation for targeting a particular MF phenotype as potential treatment for chronic liver injuries.

Single-cell sequencing reveals the evolution of immune molecules across multiple vertebrate species

INTRODUCTION

Both innate and adaptive immune system undergo evolution from low to high vertebrates. Due to the limitation of conventional approaches in identifying broader spectrum of immune cells and molecules from various vertebrates, it remains unclear how immune molecules evolve among vertebrates.

OBJECTIVES

Here, we utilized carry out comparative transcriptome analysis in various immune cells across seven vertebrate species.

METHODS

Single-cell RNA sequencing (scRNA-seq).

RESULTS

We uncovered both conserved and species-specific profiling of gene expression in innate and adaptive immunity. Macrophages exhibited highly-diversified genes and developed sophisticated molecular signaling networks along with evolution, indicating effective and versatile functions in higher species. In contrast, B cells conservatively evolved with less differentially-expressed genes in analyzed species. Interestingly, T cells represented a dominant immune cell populations in all species and unique T cell populations were identified in zebrafish and pig. We also revealed compensatory TCR cascade components utilized by different species. Inter-species comparison of core gene programs demonstrated mouse species has the highest similarity in immune transcriptomes to human.

CONCLUSIONS

Therefore, our comparative study reveals gene transcription characteristics across multiple vertebrate species during the evolution of immune system, providing insights for species-specific immunity as well as the translation of animal studies to human physiology and disease.

Comparative Analysis of Single-cell and Single-nucleus RNA-sequencing in a Rabbit Model of Retinal Detachment-related Proliferative Vitreoretinopathy

Purpose

Proliferative vitreoretinopathy (PVR) is the most common cause of failure of retinal reattachment surgery, and the molecular changes leading to this aberrant wound healing process are currently unknown. Our ultimate goal is to study PVR pathogenesis by employing single-cell transcriptomics to dissect cellular heterogeneity.

Design

Here we aimed to compare single-cell RNA sequencing (scRNA-seq)  and single-nucleus RNA-sequencing (snRNA-seq) of retinal PVR samples in the rabbit model.

Participants

Unilateral induction of PVR lesions in rabbit eyes with contralateral eyes serving as controls.

Methods

Proliferative vitreoretinopathy was induced unilaterally in Dutch Belted rabbits. At different timepoints after PVR induction, retinas were dissociated into either cells or nuclei suspension and processed for scRNA-seq or snRNA-seq.

Main Outcome Measures

Single cell and nuclei transcriptomic profiles of retinas after PVR induction.

Results

Single-cell RNA sequencing and snRNA-seq were conducted on retinas at 4 hours and 14 days after disease induction. Although the capture rate of unique molecular identifiers and genes were greater in scRNA-seq samples, overall gene expression profiles of individual cell types were highly correlated between scRNA-seq and snRNA-seq. A major disparity between the 2 sequencing modalities was the cell type capture rate, however, with glial cell types overrepresented in scRNA-seq, and inner retinal neurons were enriched by snRNA-seq. Furthermore, fibrotic Müller glia were overrepresented in snRNA-seq samples, whereas reactive Müller glia were overrepresented in scRNA-seq samples. Trajectory analyses were similar between the 2 methods, allowing for the combined analysis of the scRNA-seq and snRNA-seq data sets.

Conclusions

These findings highlight limitations of both scRNA-seq and snRNA-seq analysis and imply that use of both techniques together can more accurately identify transcriptional networks critical for aberrant fibrogenesis in PVR than using either in isolation.

Financial Disclosures

Proprietary or commercial disclosure may be found after the references.

How single-cell transcriptomics provides insight on hepatic responses to TCDD

The prototypical aryl hydrocarbon receptor (AHR) ligand, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), has been a valuable model for investigating toxicant-associated fatty liver disease (TAFLD). TCDD induces dose-dependent hepatic lipid accumulation, followed by the development of inflammatory foci and eventual progression to fibrosis in mice. Previously, bulk approaches and in vitro examination of different cell types were relied upon to study the mechanisms underlying TCDD-induced liver pathologies. However, the advent of single-cell transcriptomic technologies, such as single-nuclei RNA sequencing (snRNAseq) and spatial transcriptomics (STx), has provided new insights into the responses of hepatic cell types to TCDD exposure. This review explores the application of these single-cell transcriptomic technologies and highlights their contributions towards unraveling the cell-specific mechanisms mediating the hepatic responses to TCDD.

Profiling the genome and proteome of metabolic dysfunction-associated steatotic liver disease identifies potential therapeutic targets

BACKGROUND & AIMS

Metabolic dysfunction-associated steatotic liver disease (MASLD) affects over 25% of the population and currently has no effective treatments. Plasma proteins with causal evidence may represent promising drug targets. We aimed to identify plasma proteins in the causal pathway of MASLD and explore their interaction with obesity.

METHODS

We analysed 2,941 plasma proteins in 43,978 European participants from UK Biobank. We performed genome-wide association study (GWAS) for all MASLD-associated proteins and created the largest MASLD GWAS (109,885 cases/1,014,923 controls). We performed Mendelian Randomization (MR) and integrated proteins and their encoding genes in MASLD ranges to identify candidate causal proteins. We then validated them through independent replication, exome sequencing, liver imaging, bulk and single-cell gene expression, liver biopsies, pathway, and phenome-wide data. We explored the role of obesity by MR and multivariable MR across proteins, body mass index, and MASLD.

RESULTS

We found 929 proteins associated with MASLD, reported five novel genetic loci associated with MASLD, and identified 17 candidate MASLD protein targets. We identified four novel targets for MASLD (CD33, GRHPR, HMOX2, and SCG3), provided protein evidence supporting roles of AHCY, FCGR2B, ORM1, and RBKS in MASLD, and validated nine previously known targets. We found that CD33, FCGR2B, ORM1, RBKS, and SCG3 mediated the association of obesity and MASLD, and HMOX2, ORM1, and RBKS had effect on MASLD independent of obesity.

CONCLUSIONS

This study identified new protein targets in the causal pathway of MASLD, providing new insights into the multi-omics architecture and pathophysiology of MASLD. These findings advise further therapeutic interventions for MASLD.

A rat liver cell atlas reveals intrahepatic myeloid heterogeneity

The large size and vascular accessibility of the laboratory rat (Rattus norvegicus) make it an ideal hepatic animal model for diseases that require surgical manipulation. Often, the disease susceptibility and outcomes of inflammatory pathologies vary significantly between strains. This study uses single-cell transcriptomics to better understand the complex cellular network of the rat liver, as well as to unravel the cellular and molecular sources of inter-strain hepatic variation. We generated single-cell and single-nucleus transcriptomic maps of the livers of healthy Dark Agouti and Lewis rat strains and developed a factor analysis-based bioinformatics analysis pipeline to study data covariates, such as strain and batch. Using this approach, we discovered transcriptomic variation within the hepatocyte and myeloid populations that underlie distinct cell states between rat strains. This finding will help provide a reference for future investigations on strain-dependent outcomes of surgical experiment models.

Single-cell dynamics of liver development in postnatal pigs

The postnatal development of the liver, an essential organ for metabolism and immunity, remains poorly characterized at the single-cell resolution. Here, we generated single-nucleus and single-cell transcriptomes of 84,824 pig liver cells at four postnatal time points: day 30, 42, 150, and 730. We uncovered 23 cell types, including three rare cell types: plasmacytoid dendritic cells, CAVIN3+IGF2+ endothelial cells, and EBF1+ fibroblasts. The latter two were verified by multiplex immunohistochemistry. Trajectory and gene regulatory analyses revealed 33 genes that encode transcription factors associated with hepatocyte development and function, including NFIL3 involved in regulating hepatic metabolism. We characterized the spatiotemporal heterogeneity of liver endothelial cells, identified and validated leucine zipper protein 2 (LUZP2) as a novel adult liver sinusoidal endothelial cell-specific transcription factor. Lymphoid cells (NK and T cells) governed the immune system of the pig liver since day 30. Furthermore, we identified a cluster of tissue-resident NK cells, which displayed virus defense functions, maintained proliferative features at day 730, and manifested a higher conservative transcription factor expression pattern in humans than in mouse liver. Our study presents the most comprehensive postnatal liver development single-cell atlas and demonstrates the metabolic and immune changes across the four age stages.

Sex-biased gene expression across mammalian organ development and evolution

Sexually dimorphic traits are common among mammals and are specified during development through the deployment of sex-specific genetic programs. Because little is known about these programs, we investigated them using a resource of gene expression profiles in males and females throughout the development of five organs in five mammals (human, mouse, rat, rabbit, and opossum) and a bird (chicken). We found that sex-biased gene expression varied considerably across organs and species and was often cell-type specific. Sex differences increased abruptly around sexual maturity instead of increasing gradually during organ development. Finally, sex-biased gene expression evolved rapidly at the gene level, with differences between organs in the evolutionary mechanisms used, but more slowly at the cellular level, with the same cell types being sexually dimorphic across species.

Biliary Tract Cancer: Molecular Biology of Precursor Lesions

Biliary tract cancer is a devastating malignancy of the bile ducts and gallbladder with a dismal prognosis. The study of precancerous lesions has received considerable attention and led to a histopathological classification which, in some respects, remains an evolving field. Consequently, increasing efforts have been devoted to characterizing the molecular pathogenesis of the precursor lesions, with the aim of better understanding the mechanisms of tumor progression, and with the ultimate goal of meeting the challenges of early diagnosis and treatment. This review delves into the molecular mechanisms that initiate and promote the development of precursor lesions of intra- and extrahepatic cholangiocarcinoma and of gallbladder carcinoma. It addresses the genomic, epigenomic, and transcriptomic landscape of these precursors and provides an overview of animal and organoid models used to study them. In conclusion, this review summarizes the known molecular features of precancerous lesions in biliary tract cancer and highlights our fragmentary knowledge of the molecular pathogenesis of tumor initiation.

Steatosis drives monocyte-derived macrophage accumulation in human metabolic dysfunction-associated fatty liver disease

Background & Aims

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a common complication of obesity with a hallmark feature of hepatic steatosis. Recent data from animal models of MAFLD have demonstrated substantial changes in macrophage composition in the fatty liver. In humans, the relationship between liver macrophage heterogeneity and liver steatosis is less clear.

Methods

Liver tissue from 21 participants was collected at time of bariatric surgery and analysed using flow cytometry, immunofluorescence, and H&E microscopy. Single-cell RNA sequencing was also conducted on a subset of samples (n = 3). Intrahepatic triglyceride content was assessed via MRI and tissue histology. Mouse models of hepatic steatosis were used to investigate observations made from human liver tissue.

Results

We observed variable degrees of liver steatosis with minimal fibrosis in our participants. Single-cell RNA sequencing revealed four macrophage clusters that exist in the human fatty liver encompassing Kupffer cells and monocyte-derived macrophages (MdMs). The genes expressed in these macrophage subsets were similar to those observed in mouse models of MAFLD. Hepatic CD14+ monocyte/macrophage number correlated with the degree of steatosis. Using mouse models of early liver steatosis, we demonstrate that recruitment of MdMs precedes Kupffer cell loss and liver damage. Electron microscopy of isolated macrophages revealed increased lipid accumulation in MdMs, and ex vivo lipid transfer experiments suggested that MdMs may serve a distinct role in lipid uptake during MAFLD.

Conclusions

The human liver in MAFLD contains macrophage subsets that align well with those that appear in mouse models of fatty liver disease. Recruited myeloid cells correlate well with the degree of liver steatosis in humans. MdMs appear to participate in lipid uptake during early stages of MALFD.

Impact and implications

Metabolic dysfunction associated fatty liver disease (MAFLD) is extremely common; however, the early inflammatory responses that occur in human disease are not well understood. In this study, we investigated macrophage heterogeneity in human livers during early MAFLD and demonstrated that similar shifts in macrophage subsets occur in human disease that are similar to those seen in preclinical models. These findings are important as they establish a translational link between mouse and human models of disease, which is important for the development and testing of new therapeutic approaches for MAFLD.

Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

BACKGROUND

Xenobiotics are primarily metabolized by hepatocytes in the liver, and primary human hepatocytes are the gold standard model for the assessment of drug efficacy, safety, and toxicity in the early phases of drug development. Recent advances in single-cell genomics demonstrate liver zonation and ploidy as main drivers of cellular heterogeneity. However, little is known about the impact of hepatocyte specialization on liver function upon metabolic challenge, including hepatic metabolism, detoxification, and protein synthesis.

RESULTS

Here, we investigate the metabolic capacity of individual human hepatocytes in vitro. We assess how chronic accumulation of lipids enhances cellular heterogeneity and impairs the metabolisms of drugs. Using a phenotyping five-probe cocktail, we identify four functional subgroups of hepatocytes responding differently to drug challenge and fatty acid accumulation. These four subgroups display differential gene expression profiles upon cocktail treatment and xenobiotic metabolism-related specialization. Notably, intracellular fat accumulation leads to increased transcriptional variability and diminishes the drug-related metabolic capacity of hepatocytes.

CONCLUSIONS

Our results demonstrate that, upon a metabolic challenge such as exposure to drugs or intracellular fat accumulation, hepatocyte subgroups display different and heterogeneous transcriptional responses.

Assessing Markovian and Delay Models for Single-Nucleus RNA Sequencing

The serial nature of reactions involved in the RNA life-cycle motivates the incorporation of delays in models of transcriptional dynamics. The models couple a transcriptional process to a fairly general set of delayed monomolecular reactions with no feedback. We provide numerical strategies for calculating the RNA copy number distributions induced by these models, and solve several systems with splicing, degradation, and catalysis. An analysis of single-cell and single-nucleus RNA sequencing data using these models reveals that the kinetics of nuclear export do not appear to require invocation of a non-Markovian waiting time.

Spatial transcriptomics in development and disease

The proper functioning of diverse biological systems depends on the spatial organization of their cells, a critical factor for biological processes like shaping intricate tissue functions and precisely determining cell fate. Nonetheless, conventional bulk or single-cell RNA sequencing methods were incapable of simultaneously capturing both gene expression profiles and the spatial locations of cells. Hence, a multitude of spatially resolved technologies have emerged, offering a novel dimension for investigating regional gene expression, spatial domains, and interactions between cells. Spatial transcriptomics (ST) is a method that maps gene expression in tissue while preserving spatial information. It can reveal cellular heterogeneity, spatial organization and functional interactions in complex biological systems. ST can also complement and integrate with other omics methods to provide a more comprehensive and holistic view of biological systems at multiple levels of resolution. Since the advent of ST, new methods offering higher throughput and resolution have become available, holding significant potential to expedite fresh insights into comprehending biological complexity. Consequently, a rapid increase in associated research has occurred, using these technologies to unravel the spatial complexity during developmental processes or disease conditions. In this review, we summarize the recent advancement of ST in historical, technical, and application contexts. We compare different types of ST methods based on their principles and workflows, and present the bioinformatics tools for analyzing and integrating ST data with other modalities. We also highlight the applications of ST in various domains of biomedical research, especially development and diseases. Finally, we discuss the current limitations and challenges in the field, and propose the future directions of ST.

Friend or foe? The elusive role of hepatic stellate cells in liver cancer

Liver fibrosis is a substantial risk factor for the development and progression of liver cancer, which includes hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). Studies utilizing cell fate mapping and single-cell transcriptomics techniques have identified quiescent perisinusoidal hepatic stellate cells (HSCs) as the primary source of activated collagen-producing HSCs and liver cancer-associated fibroblasts (CAFs) in HCC and liver metastasis, complemented in iCCA by contributions from portal fibroblasts. At the same time, integrative computational analysis of single-cell, single-nucleus and spatial RNA sequencing data have revealed marked heterogeneity among HSCs and CAFs, with distinct subpopulations displaying unique gene expression signatures and functions. Some of these subpopulations have divergent roles in promoting or inhibiting liver fibrogenesis and carcinogenesis. In this Review, we discuss the dual roles of HSC subpopulations in liver fibrogenesis and their contribution to liver cancer promotion, progression and metastasis. We review the transcriptomic and functional similarities between HSC and CAF subpopulations, highlighting the pathways that either promote or prevent fibrosis and cancer, and the immunological landscape from which these pathways emerge. Insights from ongoing studies will yield novel strategies for developing biomarkers, assessing prognosis and generating new therapies for both HCC and iCCA prevention and treatment.

Oit3, a promising hallmark gene for targeting liver sinusoidal endothelial cells

Liver sinusoidal endothelial cells (LSECs) play a pivotal role in maintaining liver homeostasis and influencing the pathological processes of various liver diseases. However, neither LSEC-specific hallmark genes nor a LSEC promoter-driven Cre mouse line has been introduced before, which largely restricts the study of liver diseases with vascular disorders. To explore LSEC-specific hallmark genes, we compared the top 50 marker genes between liver endothelial cells (ECs) and liver capillary ECs and identified 18 overlapping genes. After excluding globally expressed genes and those with low expression percentages, we narrowed our focus to two final candidates: Oit3 and Dnase1l3. Through single-cell RNA sequencing (scRNA-seq) and analysis of the NCBI database, we confirmed the extrahepatic expression of Dnase1l3. The paired-cell sequencing data further demonstrated that Oit3 was predominantly expressed in the midlobular liver ECs. Subsequently, we constructed inducible Oit3-CreERT2 transgenic mice, which were further crossed with ROSA26-tdTomato mice. Microscopy validated that the established Oit3-CreERT2-tdTomato mice exhibited significant fluorescence in the liver rather than in other organs. The staining analysis confirmed the colocalization of tdTomato and EC markers. Ex-vivo experiments further confirmed that isolated tdTomato+ cells exhibited well-differentiated fenestrae and highly expressed EC markers, confirming their identity as LSECs. Overall, Oit3 is a promising hallmark gene for tracing LSECs. The establishment of Oit3-CreERT2-tdTomato mice provides a valuable model for studying the complexities of LSECs in liver diseases.

The multifaceted role of macrophages during acute liver injury

The liver is situated at the interface of the gut and circulation where it acts as a filter for blood-borne and gut-derived microbes and biological molecules, promoting tolerance of non-invasive antigens while driving immune responses against pathogenic ones. Liver resident immune cells such as Kupffer cells (KCs), a subset of macrophages, maintain homeostasis under physiological conditions. However, upon liver injury, these cells and others recruited from circulation participate in the response to injury and the repair of tissue damage. Such response is thus spatially and temporally regulated and implicates interconnected cells of immune and non-immune nature. This review will describe the hepatic immune environment during acute liver injury and the subsequent wound healing process. In its early stages, the wound healing immune response involves a necroinflammatory process characterized by partial depletion of resident KCs and lymphocytes and a significant infiltration of myeloid cells including monocyte-derived macrophages (MoMFs) complemented by a wave of pro-inflammatory mediators. The subsequent repair stage includes restoring KCs, initiating angiogenesis, renewing extracellular matrix and enhancing proliferation/activation of resident parenchymal and mesenchymal cells. This review will focus on the multifaceted role of hepatic macrophages, including KCs and MoMFs, and their spatial distribution and roles during acute liver injury.

Technical optimization of spatially resolved single-cell transcriptomic datasets to study clinical liver disease

Single cell and spatially resolved 'omic' techniques have enabled deep characterization of clinical pathologies that remain poorly understood, providing unprecedented insights into molecular mechanisms of disease. However, transcriptomic platforms are costly, limiting sample size, which increases the possibility of pre-analytical variables such as tissue processing and storage procedures impacting RNA quality and downstream analyses. Furthermore, spatial transcriptomics have not yet reached single cell resolution, leading to the development of multiple deconvolution methods to predict individual cell types within each transcriptome 'spot' on tissue sections. In this study, we performed spatial transcriptomics and single nucleus RNA sequencing (snRNASeq) on matched specimens from patients with either histologically normal or advanced fibrosis to establish important aspects of tissue handling, data processing, and downstream analyses of biobanked liver samples. We observed that tissue preservation technique impacts transcriptomic data, especially in fibrotic liver. Deconvolution of the spatial transcriptome using paired snRNASeq data generated a spatially resolved, single cell dataset with 24 unique liver cell phenotypes. We determined that cell-cell interactions predicted using ligand-receptor analysis of snRNASeq data poorly correlated with celullar relationships identified using spatial transcriptomics. Our study provides a framework for generating spatially resolved, single cell datasets to study gene expression and cell-cell interactions in biobanked clinical samples with advanced liver disease.

Efficacy of antiviral therapy and host-virus interactions visualised using serial liver sampling with fine-needle aspirates

Background & Aims

Novel therapies for chronic hepatitis B (CHB), such as RNA interference, target all viral RNAs for degradation, whereas nucleoside analogues are thought to block reverse transcription with minimal impact on viral transcripts. However, limitations in technology and sampling frequency have been obstacles to measuring actual changes in HBV transcription in the liver of patients starting therapy.

Methods

We used elective liver sampling with fine-needle aspirates (FNAs) to investigate the impact of treatment on viral replication in patients with CHB. Liver FNAs were collected from patients with CHB at baseline and 12 and 24 weeks after starting tenofovir alafenamide treatment. Liver FNAs were subjected to single-cell RNA sequencing and analysed using the Viral-Track method.

Results

HBV was the only viral genome detected and was enriched within hepatocytes. The 5' sequencing technology identified protein-specific HBV transcripts and showed that tenofovir alafenamide therapy specifically reduced pre-genomic RNA transcripts with little impact on HBsAg or HBx transcripts. Infected hepatocytes displayed unique gene signatures associated with an immunological response to viral infection.

Conclusions

Longitudinal liver sampling, combined with single-cell RNA sequencing, captured the dynamic impact of antiviral therapy on the replication status of HBV and revealed host-pathogen interactions at the transcriptional level in infected hepatocytes. This sequencing-based approach is applicable to early-stage clinical studies, enabling mechanistic studies of immunopathology and the effect of novel therapeutic interventions.

Impact and Implications

Infection-dependent transcriptional changes and the impact of antiviral therapy on viral replication can be measured in longitudinal human liver biopsies using single-cell RNA sequencing data.

Single cell genomics as a transformative approach for aquaculture research and innovation

Single cell genomics encompasses a suite of rapidly maturing technologies that measure the molecular profiles of individual cells within target samples. These approaches provide a large up-step in biological information compared to long-established 'bulk' methods that profile the average molecular profiles of all cells in a sample, and have led to transformative advances in understanding of cellular biology, particularly in humans and model organisms. The application of single cell genomics is fast expanding to non-model taxa, including aquaculture species, where numerous research applications are underway with many more envisaged. In this review, we highlight the potential transformative applications of single cell genomics in aquaculture research, considering barriers and potential solutions to the broad uptake of these technologies. Focusing on single cell transcriptomics, we outline considerations for experimental design, including the essential requirement to obtain high quality cells/nuclei for sequencing in ectothermic aquatic species. We further outline data analysis and bioinformatics considerations, tailored to studies with the under-characterized genomes of aquaculture species, where our knowledge of cellular heterogeneity and cell marker genes is immature. Overall, this review offers a useful source of knowledge for researchers aiming to apply single cell genomics to address biological challenges faced by the global aquaculture sector though an improved understanding of cell biology.

Fetal liver development and implications for liver disease pathogenesis

The metabolic, digestive and homeostatic roles of the liver are dependent on proper crosstalk and organization of hepatic cell lineages. These hepatic cell lineages are derived from their respective progenitors early in organogenesis in a spatiotemporally controlled manner, contributing to the liver's specialized and diverse microarchitecture. Advances in genomics, lineage tracing and microscopy have led to seminal discoveries in the past decade that have elucidated liver cell lineage hierarchies. In particular, single-cell genomics has enabled researchers to explore diversity within the liver, especially early in development when the application of bulk genomics was previously constrained due to the organ's small scale, resulting in low cell numbers. These discoveries have substantially advanced our understanding of cell differentiation trajectories, cell fate decisions, cell lineage plasticity and the signalling microenvironment underlying the formation of the liver. In addition, they have provided insights into the pathogenesis of liver disease and cancer, in which developmental processes participate in disease emergence and regeneration. Future work will focus on the translation of this knowledge to optimize in vitro models of liver development and fine-tune regenerative medicine strategies to treat liver disease. In this Review, we discuss the emergence of hepatic parenchymal and non-parenchymal cells, advances that have been made in in vitro modelling of liver development and draw parallels between developmental and pathological processes.

Harnessing metabolism of hepatic macrophages to aid liver regeneration

Liver regeneration is a dynamic and regulated process that involves inflammation, granulation, and tissue remodeling. Hepatic macrophages, abundantly distributed in the liver, are essential components that actively participate in each step to orchestrate liver regeneration. In the homeostatic liver, resident macrophages (Kupffer cells) acquire a tolerogenic phenotype and contribute to immunological tolerance. Following toxicity-induced damage or physical resection, Kupffer cells as well as monocyte-derived macrophages can be activated and promote an inflammatory process that supports the survival and activation of hepatic myofibroblasts and thus promotes scar tissue formation. Subsequently, these macrophages, in turn, exhibit the anti-inflammatory effects critical to extracellular matrix remodeling during the resolution stage. However, continuous damage-induced chronic inflammation generally leads to hepatic macrophage dysfunction, which exacerbates hepatocellular injury and triggers further liver fibrosis and even cirrhosis. Emerging macrophage-targeting strategies have shown efficacy in both preclinical and clinical studies. Increasing evidence indicates that metabolic rewiring provides substrates for epigenetic modification, which endows monocytes/macrophages with prolonged "innate immune memory". Therefore, it is reasonable to conceive novel therapeutic strategies for metabolically reprogramming macrophages and thus mediate a homeostatic or reparative process for hepatic inflammation management and liver regeneration.

Emerging and potential use of CRISPR in human liver disease

CRISPR is a gene editing tool adapted from naturally occurring defense systems from bacteria. It is a technology that is revolutionizing the interrogation of gene functions in driving liver disease, especially through genetic screens and by facilitating animal knockout and knockin models. It is being used in models of liver disease to identify which genes are critical for liver pathology, especially in genetic liver disease, hepatitis, and in cancer initiation and progression. It holds tremendous promise in treating human diseases directly by editing DNA. It could disable gene function in the case of expression of a maladaptive protein, such as blocking transthyretin as a therapy for amyloidosis, or to correct gene defects, such as restoring the normal functions of liver enzymes fumarylacetoacetate hydrolase or alpha-1 antitrypsin. It is also being studied for treatment of hepatitis B infection. CRISPR is an exciting, evolving technology that is facilitating gene characterization and discovery in liver disease and holds the potential to treat liver diseases safely and permanently.

A Novel Mouse Model of Combined Hepatocellular-Cholangiocarcinoma Induced by Diethylnitrosamine and Loss of Ppp2r5d

Primary liver cancer (PLC) can be classified in hepatocellular (HCC), cholangiocarcinoma (CCA), and combined hepatocellular-cholangiocarcinoma (cHCC-CCA). The molecular mechanisms involved in PLC development and phenotype decision are still not well understood. Complete deletion of Ppp2r5d, encoding the B56δ subunit of Protein Phosphatase 2A (PP2A), results in spontaneous HCC development in mice via a c-MYC-dependent mechanism. In the present study, we aimed to examine the role of Ppp2r5d in an independent mouse model of diethylnitrosamine (DEN)-induced hepatocarcinogenesis. Ppp2r5d deletion (heterozygous and homozygous) accelerated HCC development, corroborating its tumor-suppressive function in liver and suggesting Ppp2r5d may be haploinsufficient. Ppp2r5d-deficient HCCs stained positively for c-MYC, consistent with increased AKT activation in pre-malignant and tumor tissues of Ppp2r5d-deficient mice. We also found increased YAP activation in Ppp2r5d-deficient tumors. Remarkably, in older mice, Ppp2r5d deletion resulted in cHCC-CCA development in this model, with the CCA component showing increased expression of progenitor markers (SOX9 and EpCAM). Finally, we observed an upregulation of Ppp2r5d in tumors from wildtype and heterozygous mice, revealing a tumor-specific control mechanism of Ppp2r5d expression, and suggestive of the involvement of Ppp2r5d in a negative feedback regulation restricting tumor growth. Our study highlights the tumor-suppressive role of mouse PP2A-B56δ in both HCC and cHCC-CCA, which may have important implications for human PLC development and targeted treatment.

Axon guidance genes control hepatic artery development

Earlier data on liver development demonstrated that morphogenesis of the bile duct, portal mesenchyme and hepatic artery is interdependent, yet how this interdependency is orchestrated remains unknown. Here, using 2D and 3D imaging, we first describe how portal mesenchymal cells become organised to form hepatic arteries. Next, we examined intercellular signalling active during portal area development and found that axon guidance genes are dynamically expressed in developing bile ducts and portal mesenchyme. Using tissue-specific gene inactivation in mice, we show that the repulsive guidance molecule BMP co-receptor A (RGMA)/neogenin (NEO1) receptor/ligand pair is dispensable for portal area development, but that deficient roundabout 2 (ROBO2)/SLIT2 signalling in the portal mesenchyme causes reduced maturation of the vascular smooth muscle cells that form the tunica media of the hepatic artery. This arterial anomaly does not impact liver function in homeostatic conditions, but is associated with significant tissular damage following partial hepatectomy. In conclusion, our work identifies new players in development of the liver vasculature in health and liver regeneration.

Human liver single nuclear RNA sequencing implicates BMPR2, GDF15, arginine, and estrogen in portopulmonary hypertension

Portopulmonary hypertension (PoPH) is a type of pulmonary vascular disease due to portal hypertension that exhibits high morbidity and mortality. The mechanisms driving disease are unknown, and transcriptional characteristics unique to the PoPH liver remain unexplored. Here, we apply single nuclear RNA sequencing to compare cirrhotic livers from patients with and without PoPH. We identify characteristics unique to PoPH in cells surrounding the central hepatic vein, including increased growth differentiation factor signaling, enrichment of the arginine biosynthesis pathway, and differential expression of the bone morphogenic protein type II receptor and estrogen receptor type I genes. These results provide insight into the transcriptomic characteristics of the PoPH liver and mechanisms by which PoPH cellular dysfunction might contribute to pulmonary vascular remodeling.

Angiocrine Signaling in Sinusoidal Health and Disease

Liver sinusoidal endothelial cells (LSECs) are key players in maintaining hepatic homeostasis. They also play crucial roles during liver injury by communicating with liver cell types as well as immune cells and promoting portal hypertension, fibrosis, and inflammation. Cutting-edge technology, such as single cell and spatial transcriptomics, have revealed the existence of distinct LSEC subpopulations with a clear zonation in the liver. The signals released by LSECs are commonly called "angiocrine signaling." In this review, we summarize the role of angiocrine signaling in health and disease, including zonation in healthy liver, regeneration, fibrosis, portal hypertension, nonalcoholic fatty liver disease, alcohol-associated liver disease, aging, drug-induced liver injury, and ischemia/reperfusion, as well as potential therapeutic advances. In conclusion, sinusoidal endotheliopathy is recognized in liver disease and promising preclinical studies are paving the path toward LSEC-specific pharmacotherapies.

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 subchronic (4 wk) TCDD-exposed mouse liver to determine liver cell-type specificity, zonation and differential expression profiles for thousands of lncRNAs. TCDD dysregulated >4000 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 lncRNAs, 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 cell-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 metabolism. Networks were validated by the striking enrichments that predicted regulatory lncRNAs 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.

Liver in infections: a single-cell and spatial transcriptomics perspective

The liver is an immune organ that plays a vital role in the detection, capture, and clearance of pathogens and foreign antigens that invade the human body. During acute and chronic infections, the liver transforms from a tolerant to an active immune state. The defence mechanism of the liver mainly depends on a complicated network of intrahepatic and translocated immune cells and non-immune cells. Therefore, a comprehensive liver cell atlas in both healthy and diseased states is needed for new therapeutic target development and disease intervention improvement. With the development of high-throughput single-cell technology, we can now decipher heterogeneity, differentiation, and intercellular communication at the single-cell level in sophisticated organs and complicated diseases. In this concise review, we aimed to summarise the advancement of emerging high-throughput single-cell technologies and re-define our understanding of liver function towards infections, including hepatitis B virus, hepatitis C virus, Plasmodium, schistosomiasis, endotoxemia, and corona virus disease 2019 (COVID-19). We also unravel previously unknown pathogenic pathways and disease mechanisms for the development of new therapeutic targets. As high-throughput single-cell technologies mature, their integration into spatial transcriptomics, multiomics, and clinical data analysis will aid in patient stratification and in developing effective treatment plans for patients with or without liver injury due to infectious diseases.

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.