Mapping the developing human immune system across organs

Human SARS-CoV-2 challenge uncovers local and systemic response dynamics

The COVID-19 pandemic is an ongoing global health threat, yet our understanding of the dynamics of early cellular responses to this disease remains limited1. Here in our SARS-CoV-2 human challenge study, we used single-cell multi-omics profiling of nasopharyngeal swabs and blood to temporally resolve abortive, transient and sustained infections in seronegative individuals challenged with pre-Alpha SARS-CoV-2. Our analyses revealed rapid changes in cell-type proportions and dozens of highly dynamic cellular response states in epithelial and immune cells associated with specific time points and infection status. We observed that the interferon response in blood preceded the nasopharyngeal response. Moreover, nasopharyngeal immune infiltration occurred early in samples from individuals with only transient infection and later in samples from individuals with sustained infection. High expression of HLA-DQA2 before inoculation was associated with preventing sustained infection. Ciliated cells showed multiple immune responses and were most permissive for viral replication, whereas nasopharyngeal T cells and macrophages were infected non-productively. We resolved 54 T cell states, including acutely activated T cells that clonally expanded while carrying convergent SARS-CoV-2 motifs. Our new computational pipeline Cell2TCR identifies activated antigen-responding T cells based on a gene expression signature and clusters these into clonotype groups and motifs. Overall, our detailed time series data can serve as a Rosetta stone for epithelial and immune cell responses and reveals early dynamic responses associated with protection against infection.

Machine learning integrative approaches to advance computational immunology

The study of immunology, traditionally reliant on proteomics to evaluate individual immune cells, has been revolutionized by single-cell RNA sequencing. Computational immunologists play a crucial role in analysing these datasets, moving beyond traditional protein marker identification to encompass a more detailed view of cellular phenotypes and their functional roles. Recent technological advancements allow the simultaneous measurements of multiple cellular components-transcriptome, proteome, chromatin, epigenetic modifications and metabolites-within single cells, including in spatial contexts within tissues. This has led to the generation of complex multiscale datasets that can include multimodal measurements from the same cells or a mix of paired and unpaired modalities. Modern machine learning (ML) techniques allow for the integration of multiple "omics" data without the need for extensive independent modelling of each modality. This review focuses on recent advancements in ML integrative approaches applied to immunological studies. We highlight the importance of these methods in creating a unified representation of multiscale data collections, particularly for single-cell and spatial profiling technologies. Finally, we discuss the challenges of these holistic approaches and how they will be instrumental in the development of a common coordinate framework for multiscale studies, thereby accelerating research and enabling discoveries in the computational immunology field.

From whole bodies to single cells: A guide to transcriptomic approaches for ecology and evolutionary biology

RNA sequencing (RNAseq) methodology has experienced a burst of technological developments in the last decade, which has opened up opportunities for studying the mechanisms of adaptation to environmental factors at both the organismal and cellular level. Selecting the most suitable experimental approach for specific research questions and model systems can, however, be a challenge and researchers in ecology and evolution are commonly faced with the choice of whether to study gene expression variation in whole bodies, specific tissues, and/or single cells. A wide range of sometimes polarised opinions exists over which approach is best. Here, we highlight the advantages and disadvantages of each of these approaches to provide a guide to help researchers make informed decisions and maximise the power of their study. Using illustrative examples of various ecological and evolutionary research questions, we guide the readers through the different RNAseq approaches and help them identify the most suitable design for their own projects.

Mitochondrial Oxidative Stress Regulates FOXP3+ T-Cell Activity and CD4-Mediated Inflammation in Older Adults with Frailty

In healthy older adults, the immune system generally preserves its response and contributes to a long, healthy lifespan. However, rapid deterioration in immune regulation can lead to chronic inflammation, termed inflammaging, which accelerates pathological aging and diminishes the quality of life in older adults with frailty. A significant limitation in current aging research is the predominant focus on comparisons between young and older populations, often overlooking the differences between healthy older adults and those experiencing pathological aging. Our study elucidates the intricate immunological dynamics of the CD4/Treg axis in frail older adults compared to comparable age-matched healthy older adults. By utilizing publicly available RNA sequencing and single-cell RNA sequencing (scRNAseq) data from peripheral blood mononuclear cells (PBMCs), we identified a specific Treg cell subset and transcriptional landscape contributing to the dysregulation of CD4+ T-cell responses. We explored the molecular mechanisms underpinning Treg dysfunction, revealing that Tregs from frail older adults exhibit reduced mitochondrial protein levels, impairing mitochondrial oxidative phosphorylation. This impairment is driven by the TNF/NF-kappa B pathway, leading to cumulative inflammation. Further, we gained a deeper understanding of the CD4/Treg axis by predicting the effects of gene perturbations on cellular signaling networks. Collectively, these findings highlight the age-related relationship between mitochondrial dysfunction in the CD4/Treg axis and its role in accelerating aging and frailty in older adults. Targeting Treg dysfunction offers a critical basis for developing tailored therapeutic strategies aimed at improving the quality of life in older adults.

NUDCD3 deficiency disrupts V(D)J recombination to cause SCID and Omenn syndrome

Inborn errors of T cell development present a pediatric emergency in which timely curative therapy is informed by molecular diagnosis. In 11 affected patients across four consanguineous kindreds, we detected homozygosity for a single deleterious missense variant in the gene NudC domain-containing 3 (NUDCD3). Two infants had severe combined immunodeficiency with the complete absence of T and B cells (T -B- SCID), whereas nine showed classical features of Omenn syndrome (OS). Restricted antigen receptor gene usage by residual T lymphocytes suggested impaired V(D)J recombination. Patient cells showed reduced expression of NUDCD3 protein and diminished ability to support RAG-mediated recombination in vitro, which was associated with pathologic sequestration of RAG1 in the nucleoli. Although impaired V(D)J recombination in a mouse model bearing the homologous variant led to milder immunologic abnormalities, NUDCD3 is absolutely required for healthy T and B cell development in humans.

Single-cell immune repertoire analysis

Single-cell T cell and B cell antigen receptor-sequencing data analysis can potentially perform in-depth assessments of adaptive immune cells that inform on understanding immune cell development to tracking clonal expansion in disease and therapy. However, it has been extremely challenging to analyze and interpret T cells and B cells and their adaptive immune receptor repertoires at the single-cell level due to not only the complexity of the data but also the underlying biology. In this Review, we delve into the computational breakthroughs that have transformed the analysis of single-cell T cell and B cell antigen receptor-sequencing data.

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.

A multi-organ map of the human immune system across age, sex and ethnicity

Understanding tissue biology's heterogeneity is crucial for advancing precision medicine. Despite the centrality of the immune system in tissue homeostasis, a detailed and comprehensive map of immune cell distribution and interactions across human tissues and demographics remains elusive. To fill this gap, we harmonised data from 12,981 single-cell RNA sequencing samples and curated 29 million cells from 45 anatomical sites to create a comprehensive compositional and transcriptional healthy map of the healthy immune system. We used this resource and a novel multilevel modelling approach to track immune ageing and test differences across sex and ethnicity. We uncovered conserved and tissue-specific immune-ageing programs, resolved sex-dependent differential ageing and identified ethnic diversity in clinically critical immune checkpoints. This study provides a quantitative baseline of the immune system, facilitating advances in precision medicine. By sharing our immune map, we hope to catalyse further breakthroughs in cancer, infectious disease, immunology and precision medicine.

Transposable elements regulate thymus development and function

Transposable elements (TEs) are repetitive sequences representing ~45% of the human and mouse genomes and are highly expressed by medullary thymic epithelial cells (mTECs). In this study, we investigated the role of TEs on T-cell development in the thymus. We performed multiomic analyses of TEs in human and mouse thymic cells to elucidate their role in T-cell development. We report that TE expression in the human thymus is high and shows extensive age- and cell lineage-related variations. TE expression correlates with multiple transcription factors in all cell types of the human thymus. Two cell types express particularly broad TE repertoires: mTECs and plasmacytoid dendritic cells (pDCs). In mTECs, transcriptomic data suggest that TEs interact with transcription factors essential for mTEC development and function (e.g., PAX1 and REL), and immunopeptidomic data showed that TEs generate MHC-I-associated peptides implicated in thymocyte education. Notably, AIRE, FEZF2, and CHD4 regulate small yet non-redundant sets of TEs in murine mTECs. Human thymic pDCs homogenously express large numbers of TEs that likely form dsRNA, which can activate innate immune receptors, potentially explaining why thymic pDCs constitutively secrete IFN ɑ/β. This study highlights the diversity of interactions between TEs and the adaptive immune system. TEs are genetic parasites, and the two thymic cell types most affected by TEs (mTEcs and pDCs) are essential to establishing central T-cell tolerance. Therefore, we propose that orchestrating TE expression in thymic cells is critical to prevent autoimmunity in vertebrates.

A protective role for B-1 cells and oxidation-specific epitope IgM in lung fibrosis

Idiopathic pulmonary fibrosis (IPF) is a morbid fibrotic lung disease with limited treatment options. The pathophysiology of IPF remains poorly understood, and elucidation of the cellular and molecular mechanisms of IPF pathogenesis is key to the development of new therapeutics. B-1 cells are an innate B cell population which play an important role linking innate and adaptive immunity. B-1 cells spontaneously secrete natural IgM and prevent inflammation in several disease states. One class of these IgM recognize oxidation-specific epitopes (OSE), which have been shown to be generated in lung injury and to promote fibrosis. A main B-1 cell reservoir is the pleural space, adjacent to the typical distribution of fibrosis in IPF. In this study, we demonstrate that B-1 cells are recruited to the lung during injury where they secrete IgM to OSE (IgM OSE ). We also show that the pleural B-1 cell reservoir responds to lung injury through regulation of the chemokine receptor CXCR4. Mechanistically we show that the transcription factor Id3 is a novel negative regulator of CXCR4 expression. Using mice with B-cell specific Id3 deficiency, a model of increased B-1b cells, we demonstrate decreased bleomycin-induced fibrosis compared to littermate controls. Furthermore, we show that mice deficient in secretory IgM ( sIgM -/- ) have higher mortality in response to bleomycin-induced lung injury, which is partially mitigated through airway delivery of the IgM OSE E06. Additionally, we provide insight into potential mechanisms of IgM in attenuation of fibrosis through RNA sequencing and pathway analysis, highlighting complement activation and extracellular matrix deposition as key differentially regulated pathways.

The role of B-1 cells in cancer progression and anti-tumor immunity

In recent years, in addition to the well-established role of T cells in controlling or promoting tumor growth, a new wave of research has demonstrated the active involvement of B cells in tumor immunity. B-cell subsets with distinct phenotypes and functions play various roles in tumor progression. Plasma cells and activated B cells have been linked to improved clinical outcomes in several types of cancer, whereas regulatory B cells have been associated with disease progression. However, we are only beginning to understand the role of a particular innate subset of B cells, referred to as B-1 cells, in cancer. Here, we summarize the characteristics of B-1 cells and review their ability to infiltrate tumors. We also describe the potential mechanisms through which B-1 cells suppress anti-tumor immune responses and promote tumor progression. Additionally, we highlight recent studies on the protective anti-tumor function of B-1 cells in both mouse models and humans. Understanding the functions of B-1 cells in tumor immunity could pave the way for designing more effective cancer immunotherapies.

Approaches for studying human macrophages

Macrophages are vital tissue components involved in organogenesis, maintaining homeostasis, and responses to disease. Mouse models have significantly improved our understanding of macrophages. Further investigations into the characteristics and development of human macrophages are crucial, considering the substantial anatomical and physiological distinctions between mice and humans. Despite challenges in human macrophage research, recent studies are shedding light on the ontogeny and function of human macrophages. In this opinion, we propose combinations of cutting-edge approaches to examine the diversity, development, niche, and function of human tissue-resident macrophages. These methodologies can facilitate our exploration of human macrophages more efficiently, ideally providing new therapeutic avenues for macrophage-relevant disorders.

Immune microniches shape intestinal Treg function

The intestinal immune system is highly adapted to maintaining tolerance to the commensal microbiota and self-antigens while defending against invading pathogens1,2. Recognizing how the diverse network of local cells establish homeostasis and maintains it in the complex immune environment of the gut is critical to understanding how tolerance can be re-established following dysfunction, such as in inflammatory disorders. Although cell and molecular interactions that control T regulatory (Treg) cell development and function have been identified3,4, less is known about the cellular neighbourhoods and spatial compartmentalization that shapes microorganism-reactive Treg cell function. Here we used in vivo live imaging, photo-activation-guided single-cell RNA sequencing5-7 and spatial transcriptomics to follow the natural history of T cells that are reactive towards Helicobacter hepaticus through space and time in the settings of tolerance and inflammation. Although antigen stimulation can occur anywhere in the tissue, the lamina propria-but not embedded lymphoid aggregates-is the key microniche that supports effector Treg (eTreg) cell function. eTreg cells are stable once their niche is established; however, unleashing inflammation breaks down compartmentalization, leading to dominance of CD103+SIRPα+ dendritic cells in the lamina propria. We identify and validate the putative tolerogenic interaction between CD206+ macrophages and eTreg cells in the lamina propria and identify receptor-ligand pairs that are likely to govern the interaction. Our results reveal a spatial mechanism of tolerance in the lamina propria and demonstrate how knowledge of local interactions may contribute to the next generation of tolerance-inducing therapies.

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.

Multi-organ single-cell transcriptomics of immune cells uncovered organ-specific gene expression and functions

Despite the wealth of publicly available single-cell datasets, our understanding of distinct resident immune cells and their unique features in diverse human organs remains limited. To address this, we compiled a meta-analysis dataset of 114,275 CD45+ immune cells sourced from 14 organs in healthy donors. While the transcriptome of immune cells remains relatively consistent across organs, our analysis has unveiled organ-specific gene expression differences (GTPX3 in kidney, DNTT and ACVR2B in thymus). These alterations are linked to different transcriptional factor activities and pathways including metabolism. TNF-α signaling through the NFkB pathway was found in several organs and immune compartments. The presence of distinct expression profiles for NFkB family genes and their target genes, including cytokines, underscores their pivotal role in cell positioning. Taken together, immune cells serve a dual role: safeguarding the organs and dynamically adjusting to the intricacies of the host organ environment, thereby actively contributing to its functionality and overall homeostasis.

Advances in immunotherapy for biliary tract cancers

ABSTRACT

Biliary tract cancers (BTC), a heterogeneous disease with poor prognosis, including gallbladder cancer (GBC), intrahepatic cholangiocarcinoma (ICC), and extrahepatic cholangiocarcinoma (ECC). Although surgery is currently the primary regimen to treat BTC, most BTC patients are diagnosed at an advanced stage and miss the opportunity of surgical eradication. As a result, non-surgical therapy serves as the main intervention for advanced BTC. In recent years, immunotherapy has emerged as one of the most promising therapies in a number of solid cancers, and it includes immune checkpoint inhibitors (ICIs) monotherapy or combined therapy, tumor vaccines, oncolytic virus immunotherapy, adoptive cell therapy (ACT), and cytokine therapy. However, these therapies have been practiced in limited clinical settings in patients with BTC. In this review, we focus on the discussion of latest advances of immunotherapy in BTC and update the progress of multiple current clinical trials with different immunotherapies.

BANKSY unifies cell typing and tissue domain segmentation for scalable spatial omics data analysis

Spatial omics data are clustered to define both cell types and tissue domains. We present Building Aggregates with a Neighborhood Kernel and Spatial Yardstick (BANKSY), an algorithm that unifies these two spatial clustering problems by embedding cells in a product space of their own and the local neighborhood transcriptome, representing cell state and microenvironment, respectively. BANKSY's spatial feature augmentation strategy improved performance on both tasks when tested on diverse RNA (imaging, sequencing) and protein (imaging) datasets. BANKSY revealed unexpected niche-dependent cell states in the mouse brain and outperformed competing methods on domain segmentation and cell typing benchmarks. BANKSY can also be used for quality control of spatial transcriptomics data and for spatially aware batch effect correction. Importantly, it is substantially faster and more scalable than existing methods, enabling the processing of millions of cell datasets. In summary, BANKSY provides an accurate, biologically motivated, scalable and versatile framework for analyzing spatially resolved omics data.

Comparative transcriptomics coupled to developmental grading via transgenic zebrafish reporter strains identifies conserved features in neutrophil maturation

Neutrophils are evolutionarily conserved innate immune cells playing pivotal roles in host defense. Zebrafish models have contributed substantially to our understanding of neutrophil functions but similarities to human neutrophil maturation have not been systematically characterized, which limits their applicability to studying human disease. Here we show, by generating and analysing transgenic zebrafish strains representing distinct neutrophil differentiation stages, a high-resolution transcriptional profile of neutrophil maturation. We link gene expression at each stage to characteristic transcription factors, including C/ebp-β, which is important for late neutrophil maturation. Cross-species comparison of zebrafish, mouse, and human samples confirms high molecular similarity of immature stages and discriminates zebrafish-specific from pan-species gene signatures. Applying the pan-species neutrophil maturation signature to RNA-sequencing data from human neuroblastoma patients reveals association between metastatic tumor cell infiltration in the bone marrow and an overall increase in mature neutrophils. Our detailed neutrophil maturation atlas thus provides a valuable resource for studying neutrophil function at different stages across species in health and disease.

Mapping Cell Atlases at the Single-Cell Level

Recent advancements in single-cell technologies have led to rapid developments in the construction of cell atlases. These atlases have the potential to provide detailed information about every cell type in different organisms, enabling the characterization of cellular diversity at the single-cell level. Global efforts in developing comprehensive cell atlases have profound implications for both basic research and clinical applications. This review provides a broad overview of the cellular diversity and dynamics across various biological systems. In addition, the incorporation of machine learning techniques into cell atlas analyses opens up exciting prospects for the field of integrative biology.

STIGMA: Single-cell tissue-specific gene prioritization using machine learning

Clinical exome and genome sequencing have revolutionized the understanding of human disease genetics. Yet many genes remain functionally uncharacterized, complicating the establishment of causal disease links for genetic variants. While several scoring methods have been devised to prioritize these candidate genes, these methods fall short of capturing the expression heterogeneity across cell subpopulations within tissues. Here, we introduce single-cell tissue-specific gene prioritization using machine learning (STIGMA), an approach that leverages single-cell RNA-seq (scRNA-seq) data to prioritize candidate genes associated with rare congenital diseases. STIGMA prioritizes genes by learning the temporal dynamics of gene expression across cell types during healthy organogenesis. To assess the efficacy of our framework, we applied STIGMA to mouse limb and human fetal heart scRNA-seq datasets. In a cohort of individuals with congenital limb malformation, STIGMA prioritized 469 variants in 345 genes, with UBA2 as a notable example. For congenital heart defects, we detected 34 genes harboring nonsynonymous de novo variants (nsDNVs) in two or more individuals from a set of 7,958 individuals, including the ortholog of Prdm1, which is associated with hypoplastic left ventricle and hypoplastic aortic arch. Overall, our findings demonstrate that STIGMA effectively prioritizes tissue-specific candidate genes by utilizing single-cell transcriptome data. The ability to capture the heterogeneity of gene expression across cell populations makes STIGMA a powerful tool for the discovery of disease-associated genes and facilitates the identification of causal variants underlying human genetic disorders.

StemDriver: a knowledgebase of gene functions for hematopoietic stem cell fate determination

StemDriver is a comprehensive knowledgebase dedicated to the functional annotation of genes participating in the determination of hematopoietic stem cell fate, available at http://biomedbdc.wchscu.cn/StemDriver/. By utilizing single-cell RNA sequencing data, StemDriver has successfully assembled a comprehensive lineage map of hematopoiesis, capturing the entire continuum from the initial formation of hematopoietic stem cells to the fully developed mature cells. Extensive exploration and characterization were conducted on gene expression features corresponding to each lineage commitment. At the current version, StemDriver integrates data from 42 studies, encompassing a diverse range of 14 tissue types spanning from the embryonic phase to adulthood. In order to ensure uniformity and reliability, all data undergo a standardized pipeline, which includes quality data pre-processing, cell type annotation, differential gene expression analysis, identification of gene categories correlated with differentiation, analysis of highly variable genes along pseudo-time, and exploration of gene expression regulatory networks. In total, StemDriver assessed the function of 23 839 genes for human samples and 29 533 genes for mouse samples. Simultaneously, StemDriver also provided users with reference datasets and models for cell annotation. We believe that StemDriver will offer valuable assistance to research focused on cellular development and hematopoiesis.

CROST: a comprehensive repository of spatial transcriptomics

The development of spatial transcriptome sequencing technology has revolutionized our comprehension of complex tissues and propelled life and health sciences into an era of spatial omics. However, the current availability of databases for accessing and analyzing spatial transcriptomic data is limited. In response, we have established CROST (https://ngdc.cncb.ac.cn/crost), a comprehensive repository of spatial transcriptomics. CROST encompasses high-quality samples and houses 182 spatial transcriptomic datasets from diverse species, organs, and diseases, comprising 1033 sub-datasets and 48 043 tumor-related spatially variable genes (SVGs). Additionally, it encompasses a standardized spatial transcriptome data processing pipeline, integrates single-cell RNA sequencing deconvolution spatial transcriptomics data, and evaluates correlation, colocalization, intercellular communication, and biological function annotation analyses. Moreover, CROST integrates the transcriptome, epigenome, and genome to explore tumor-associated SVGs and provides a comprehensive understanding of their roles in cancer progression and prognosis. Furthermore, CROST provides two online tools, single-sample gene set enrichment analysis and SpatialAP, for users to annotate and analyze the uploaded spatial transcriptomics data. The user-friendly interface of CROST facilitates browsing, searching, analyzing, visualizing, and downloading desired information. Collectively, CROST offers fresh and comprehensive insights into tissue structure and a foundation for understanding multiple biological mechanisms in diseases, particularly in tumor tissues.

Dandelion uses the single-cell adaptive immune receptor repertoire to explore lymphocyte developmental origins

Assessment of single-cell gene expression (single-cell RNA sequencing) and adaptive immune receptor (AIR) sequencing (scVDJ-seq) has been invaluable in studying lymphocyte biology. Here we introduce Dandelion, a computational pipeline for scVDJ-seq analysis. It enables the application of standard V(D)J analysis workflows to single-cell datasets, delivering improved V(D)J contig annotation and the identification of nonproductive and partially spliced contigs. We devised a strategy to create an AIR feature space that can be used for both differential V(D)J usage analysis and pseudotime trajectory inference. The application of Dandelion improved the alignment of human thymic development trajectories of double-positive T cells to mature single-positive CD4/CD8 T cells, generating predictions of factors regulating lineage commitment. Dandelion analysis of other cell compartments provided insights into the origins of human B1 cells and ILC/NK cell development, illustrating the power of our approach. Dandelion is available at https://www.github.com/zktuong/dandelion .

SINGLE-CELL TRANSCRIPTOME ANALYSIS IN HEALTH AND DISEASE

ABSTRACT

The analysis of the single-cell transcriptome has emerged as a powerful tool to gain insights on the basic mechanisms of health and disease. It is widely used to reveal the cellular diversity and complexity of tissues at cellular resolution by RNA sequencing of the whole transcriptome from a single cell. Equally, it is applied to discover an unknown, rare population of cells in the tissue. The prime advantage of single-cell transcriptome analysis is the detection of stochastic nature of gene expression of the cell in tissue. Moreover, the availability of multiple platforms for the single-cell transcriptome has broadened its approaches to using cells of different sizes and shapes, including the capture of short or full-length transcripts, which is helpful in the analysis of challenging biological samples. And with the development of numerous packages in R and Python, new directions in the computational analysis of single-cell transcriptomes can be taken to characterize healthy versus diseased tissues to obtain novel pathological insights. Downstream analysis such as differential gene expression analysis, gene ontology term analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, cell-cell interaction analysis, and trajectory analysis has become standard practice in the workflow of single-cell transcriptome analysis to further examine the biology of different cell types. Here, we provide a broad overview of single-cell transcriptome analysis in health and disease conditions currently applied in various studies.

A distinct human cell type expressing MHCII and RORγt with dual characteristics of dendritic cells and type 3 innate lymphoid cells

Recent studies have characterized various mouse antigen-presenting cells (APCs) expressing the lymphoid-lineage transcription factor RORγt (Retinoid-related orphan receptor gamma t), which exhibit distinct phenotypic features and are implicated in the induction of peripheral regulatory T cells (Tregs) and immune tolerance to microbiota and self-antigens. These APCs encompass Janus cells and Thetis cell subsets, some of which express the AutoImmune REgulator (AIRE). RORγt+ MHCII+ type 3 innate lymphoid cells (ILC3) have also been implicated in the instruction of microbiota-specific Tregs. While RORγt+ APCs have been actively investigated in mice, the identity and function of these cell subsets in humans remain elusive. Herein, we identify a rare subset of RORγt+ cells with dendritic cell (DC) features through integrated single-cell RNA sequencing and single-cell ATAC sequencing. These cells, which we term RORγt+ DC-like cells (R-DC-like), exhibit DC morphology, express the MHC class II machinery, and are distinct from all previously reported DC and ILC3 subsets, but share transcriptional and epigenetic similarities with DC2 and ILC3. We have developed procedures to isolate and expand them in vitro, enabling their functional characterization. R-DC-like cells proliferate in vitro, continue to express RORγt, and differentiate into CD1c+ DC2-like cells. They stimulate the proliferation of allogeneic T cells. The identification of human R-DC-like cells with proliferative potential and plasticity toward CD1c+ DC2-like cells will prompt further investigation into their impact on immune homeostasis, inflammation, and autoimmunity.

Early human lung immune cell development and its role in epithelial cell fate

Studies of human lung development have focused on epithelial and mesenchymal cell types and function, but much less is known about the developing lung immune cells, even though the airways are a major site of mucosal immunity after birth. An unanswered question is whether tissue-resident immune cells play a role in shaping the tissue as it develops in utero. Here, we profiled human embryonic and fetal lung immune cells using scRNA-seq, smFISH, and immunohistochemistry. At the embryonic stage, we observed an early wave of innate immune cells, including innate lymphoid cells, natural killer cells, myeloid cells, and lineage progenitors. By the canalicular stage, we detected naive T lymphocytes expressing high levels of cytotoxicity genes and the presence of mature B lymphocytes, including B-1 cells. Our analysis suggests that fetal lungs provide a niche for full B cell maturation. Given the presence and diversity of immune cells during development, we also investigated their possible effect on epithelial maturation. We found that IL-1β drives epithelial progenitor exit from self-renewal and differentiation to basal cells in vitro. In vivo, IL-1β-producing myeloid cells were found throughout the lung and adjacent to epithelial tips, suggesting that immune cells may direct human lung epithelial development.

Human VH4-34 antibodies derived from B1 cells are more frequently autoreactive than VH4-34 antibodies derived from memory cells

Human B1 cells produce natural antibodies characterized by overutilization of heavy chain variable region VH4-34 in comparison to other B cell populations. VH4-34-containing antibodies have been reported to be autoreactive and to be associated with lupus and other autoimmune dyscrasias. However, it has been unclear to what extent VH4-34 antibodies manifest autoreactivity in B1 cells or other B cell populations-in other words, are VH4-34 containing antibodies autoreactive wherever found, or mainly within the B1 cell population? To address this issue we sort purified single human B1 and memory B cells and then amplified, sequenced, cloned and expressed VH4-34-containing antibodies from 76 individual B cells. Each of these antibodies was tested for autoreactivity by HEp-2 IFA and autoantigen ELISA. Antibodies were scored as autoreactive if positive by either assay. We found VH4-34 antibodies rescued from B1 cells were much more frequently autoreactive (14/48) than VH4-34 antibodies rescued from memory B cells (2/28). Among B1 cell antibodies, 4 were HEp-2+, 6 were dsDNA+ and 4 were positive for both. Considering only HEp-2+ antibodies, again these were found more frequently among B1 cell VH4-34 antibodies (8/48) than memory B cell VH4-34 antibodies (1/28). We found autoreactivity was associated with greater CDR3 length, as expected; however, we found no association between autoreactivity and a previously described FR1 "hydrophobic patch". Our results indicate that autoreactive VH4-34-containing antibodies tend to reside within the human B1 cell population.

Characterization of human pluripotent stem cell differentiation by single-cell dual-omics analyses

In vivo differentiation of human pluripotent stem cells (hPSCs) has unique advantages, such as multilineage differentiation, angiogenesis, and close cell-cell interactions. To systematically investigate multilineage differentiation mechanisms of hPSCs, we constructed the in vivo hPSC differentiation landscape containing 239,670 cells using teratoma models. We identified 43 cell types, inferred 18 cell differentiation trajectories, and characterized common and specific gene regulation patterns during hPSC differentiation at both transcriptional and epigenetic levels. Additionally, we developed the developmental single-cell Basic Local Alignment Search Tool (dscBLAST), an R-based cell identification tool, to simplify the identification processes of developmental cells. Using dscBLAST, we aligned cells in multiple differentiation models to normally developing cells to further understand their differentiation states. Overall, our study offers new insights into stem cell differentiation and human embryonic development; dscBLAST shows favorable cell identification performance, providing a powerful identification tool for developmental cells.

Large-scale single-cell RNA sequencing atlases of human immune cells across lifespan: Possibilities and challenges

Single-cell RNA sequencing technologies have successfully been leveraged for immunological insights into human prenatal, pediatric, and adult tissues. These single-cell studies have led to breakthroughs in our understanding of stem, myeloid, and lymphoid cell function. Computational analysis of fetal hematopoietic tissues has uncovered trajectories for T- and B-cell differentiation across multiple organ sites, and how these trajectories might be dysregulated in fetal and pediatric health and disease. As we enter the age of large-scale, multiomic, and integrative single-cell meta-analysis, we assess the advances and challenges of large-scale data generation, analysis, and reanalysis, and data dissemination for a broad range of scientific and clinical communities. We discuss Findable, Accessible, Interoperable, and Reusable data sharing and unified cell ontology languages as strategic areas for progress of the field in the near future. We also reflect on the trend toward deployment of multiomic and spatial genomic platforms within single-cell RNA sequencing projects, and the crucial role these data types will assume in the immediate future toward creation of comprehensive and rich single-cell atlases. We demonstrate using our recent studies of human prenatal and adult hematopoietic tissues the importance of interdisciplinary and collaborative working in science to reveal biological insights in parallel with technological and computational innovations.

scDREAMER for atlas-level integration of single-cell datasets using deep generative model paired with adversarial classifier

Integration of heterogeneous single-cell sequencing datasets generated across multiple tissue locations, time, and conditions is essential for a comprehensive understanding of the cellular states and expression programs underlying complex biological systems. Here, we present scDREAMER ( https://github.com/Zafar-Lab/scDREAMER ), a data-integration framework that employs deep generative models and adversarial training for both unsupervised and supervised (scDREAMER-Sup) integration of multiple batches. Using six real benchmarking datasets, we demonstrate that scDREAMER can overcome critical challenges including skewed cell type distribution among batches, nested batch-effects, large number of batches and conservation of development trajectory across batches. Our experiments also show that scDREAMER and scDREAMER-Sup outperform state-of-the-art unsupervised and supervised integration methods respectively in batch-correction and conservation of biological variation. Using a 1 million cells dataset, we demonstrate that scDREAMER is scalable and can perform atlas-level cross-species (e.g., human and mouse) integration while being faster than other deep-learning-based methods.

Zfp281 and Zfp148 control CD4+ T cell thymic development and TH2 functions

How CD4+ lineage gene expression is initiated in differentiating thymocytes remains poorly understood. Here, we show that the paralog transcription factors Zfp281 and Zfp148 control both this process and cytokine expression by T helper cell type 2 (TH2) effector cells. Genetic, single-cell, and spatial transcriptomic analyses showed that these factors promote the intrathymic CD4+ T cell differentiation of class II major histocompatibility complex (MHC II)-restricted thymocytes, including expression of the CD4+ lineage-committing factor Thpok. In peripheral T cells, Zfp281 and Zfp148 promoted chromatin opening at and expression of TH2 cytokine genes but not of the TH2 lineage-determining transcription factor Gata3. We found that Zfp281 interacts with Gata3 and is recruited to Gata3 genomic binding sites at loci encoding Thpok and TH2 cytokines. Thus, Zfp148 and Zfp281 collaborate with Gata3 to promote CD4+ T cell development and TH2 cell responses.

Splenic stromal niches in homeostasis and immunity

The spleen is a gatekeeper of systemic immunity where immune responses against blood-borne pathogens are initiated and sustained. Non-haematopoietic stromal cells construct microanatomical niches in the spleen that make diverse contributions to physiological spleen functions and regulate the homeostasis of immune cells. Additional signals from spleen autonomic nerves also modify immune responses. Recent insight into the diversity of the splenic fibroblastic stromal cells has revised our understanding of how these cells help to orchestrate splenic responses to infection and contribute to immune responses. In this Review, we examine our current understanding of how stromal niches and neuroimmune circuits direct the immunological functions of the spleen, with a focus on T cell immunity.

Precise identification of cell states altered in disease using healthy single-cell references

Joint analysis of single-cell genomics data from diseased tissues and a healthy reference can reveal altered cell states. We investigate whether integrated collections of data from healthy individuals (cell atlases) are suitable references for disease-state identification and whether matched control samples are needed to minimize false discoveries. We demonstrate that using a reference atlas for latent space learning followed by differential analysis against matched controls leads to improved identification of disease-associated cells, especially with multiple perturbed cell types. Additionally, when an atlas is available, reducing control sample numbers does not increase false discovery rates. Jointly analyzing data from a COVID-19 cohort and a blood cell atlas, we improve detection of infection-related cell states linked to distinct clinical severities. Similarly, we studied disease states in pulmonary fibrosis using a healthy lung atlas, characterizing two distinct aberrant basal states. Our analysis provides guidelines for designing disease cohort studies and optimizing cell atlas use.

MAGNETO: Cell type marker panel generator from single-cell transcriptomic data

Single-cell RNA sequencing experiments produce data useful to identify different cell types, including uncharacterized and rare ones. This enables us to study the specific functional roles of these cells in different microenvironments and contexts. After identifying a (novel) cell type of interest, it is essential to build succinct marker panels, composed of a few genes referring to cell surface proteins and clusters of differentiation molecules, able to discriminate the desired cells from the other cell populations. In this work, we propose a fully-automatic framework called MAGNETO, which can help construct optimal marker panels starting from a single-cell gene expression matrix and a cell type identity for each cell. MAGNETO builds effective marker panels solving a tailored bi-objective optimization problem, where the first objective regards the identification of the genes able to isolate a specific cell type, while the second conflicting objective concerns the minimization of the total number of genes included in the panel. Our results on three public datasets show that MAGNETO can identify marker panels that identify the cell populations of interest better than state-of-the-art approaches. Finally, by fine-tuning MAGNETO, our results demonstrate that it is possible to obtain marker panels with different specificity levels.

A spatial human thymus cell atlas mapped to a continuous tissue axis

T cells develop from circulating precursors, which enter the thymus and migrate throughout specialised sub-compartments to support maturation and selection. This process starts already in early fetal development and is highly active until the involution of the thymus in adolescence. To map the micro-anatomical underpinnings of this process in pre- vs. post-natal states, we undertook a spatially resolved analysis and established a new quantitative morphological framework for the thymus, the Cortico-Medullary Axis. Using this axis in conjunction with the curation of a multimodal single-cell, spatial transcriptomics and high-resolution multiplex imaging atlas, we show that canonical thymocyte trajectories and thymic epithelial cells are highly organised and fully established by post-conception week 12, pinpoint TEC progenitor states, find that TEC subsets and peripheral tissue genes are associated with Hassall's Corpuscles and uncover divergence in the pace and drivers of medullary entry between CD4 vs. CD8 T cell lineages. These findings are complemented with a holistic toolkit for spatial analysis and annotation, providing a basis for a detailed understanding of T lymphocyte development.

Multimodal cartography of human lymphopoiesis reveals B and T/NK/ILC lineages are subjected to differential regulation

The developmental cartography of human lymphopoiesis remains incompletely understood. Here, we establish a multimodal map demonstrating that lymphoid specification follows independent direct or stepwise hierarchic routes converging toward the emergence of newly characterized CD117lo multi-lymphoid progenitors (MLPs) that undergo a proliferation arrest before entering the CD127- (NK/ILC/T) or CD127+ (B) lymphoid pathways. While the differentiation of CD127- early lymphoid progenitors is mainly driven by Flt3 signaling, emergence of their CD127+ counterparts is regulated cell-intrinsically and depends exclusively on the divisional history of their upstream precursors, including hematopoietic stem cells. Further, transcriptional mapping of differentiation trajectories reveals that whereas myeloid granulomonocytic lineages follow continuous differentiation pathways, lymphoid trajectories are intrinsically discontinuous and characterized by sequential waves of cell proliferation allowing pre-commitment amplification of lymphoid progenitor pools. Besides identifying new lymphoid specification pathways and regulatory checkpoints, our results demonstrate that NK/ILC/T and B lineages are under fundamentally distinct modes of regulation. (149 words).

Decoding Human Biology and Disease Using Single-cell Omics Technologies

Over the past decade, advances in single-cell omics (SCO) technologies have enabled the investigation of cellular heterogeneity at an unprecedented resolution and scale, opening a new avenue for understanding human biology and disease. In this review, we summarize the developments of sequencing-based SCO technologies and computational methods, and focus on considerable insights acquired from SCO sequencing studies to understand normal and diseased properties, with a particular emphasis on cancer research. We also discuss the technological improvements of SCO and its possible contribution to fundamental research of the human, as well as its great potential in clinical diagnoses and personalized therapies of human disease.

An immune cell atlas reveals the dynamics of human macrophage specification during prenatal development

Macrophages are heterogeneous and play critical roles in development and disease, but their diversity, function, and specification remain inadequately understood during human development. We generated a single-cell RNA sequencing map of the dynamics of human macrophage specification from PCW 4-26 across 19 tissues. We identified a microglia-like population and a proangiogenic population in 15 macrophage subtypes. Microglia-like cells, molecularly and morphologically similar to microglia in the CNS, are present in the fetal epidermis, testicle, and heart. They are the major immune population in the early epidermis, exhibit a polarized distribution along the dorsal-lateral-ventral axis, and interact with neural crest cells, modulating their differentiation along the melanocyte lineage. Through spatial and differentiation trajectory analysis, we also showed that proangiogenic macrophages are perivascular across fetal organs and likely yolk-sac-derived as microglia. Our study provides a comprehensive map of the heterogeneity and developmental dynamics of human macrophages and unravels their diverse functions during development.

Single-cell assignment using multiple-adversarial domain adaptation network with large-scale references

The rapid accumulation of single-cell RNA-seq data has provided rich resources to characterize various human cell populations. However, achieving accurate cell-type annotation using public references presents challenges due to inconsistent annotations, batch effects, and rare cell types. Here, we introduce SELINA (single-cell identity navigator), an integrative and automatic cell-type annotation framework based on a pre-curated reference atlas spanning various tissues. SELINA employs a multiple-adversarial domain adaptation network to remove batch effects within the reference dataset. Additionally, it enhances the annotation of less frequent cell types by synthetic minority oversampling and fits query data with the reference data using an autoencoder. SELINA culminates in the creation of a comprehensive and uniform reference atlas, encompassing 1.7 million cells covering 230 distinct human cell types. We substantiate its robustness and superiority across a multitude of human tissues. Notably, SELINA could accurately annotate cells within diverse disease contexts. SELINA provides a complete solution for human single-cell RNA-seq data annotation with both python and R packages.

Transendothelial Migration of Human B Cells: Chemokine versus Antigen

B cells, like T cells, can infiltrate sites of inflammation, but the processes and B cell subsets involved are poorly understood. Using human cells and in vitro assays, we find only a very small number of B cells will adhere to TNF-activated (but not to resting) human microvascular endothelial cells (ECs) under conditions of venular flow and do so by binding to ICAM-1 and VCAM-1. CXCL13 and, to a lesser extent, CXCL10 bound to the ECs can increase adhesion and induce transendothelial migration (TEM) of adherent naive and memory B cells in 10-15 min through a process involving cell spreading, translocation of the microtubule organizing center (MTOC) into a trailing uropod, and interacting with EC activated leukocyte cell adhesion molecule. Engagement of the BCR by EC-bound anti-κ L chain Ab also increases adhesion and TEM of κ+ but not λ+ B cells. BCR-induced TEM takes 30-60 min, requires Syk activation, is initiated by B cell rounding up and translocation of the microtubule organizing center to the region of the B cell adjacent to the EC, and also uses EC activated leukocyte cell adhesion molecule for TEM. BCR engagement reduces the number of B cells responding to chemokines and preferentially stimulates TEM of CD27+ B cells that coexpress IgD, with or without IgM, as well as CD43. RNA-sequencing analysis suggests that peripheral blood CD19+CD27+CD43+IgD+ cells have increased expression of genes that support BCR activation as well as innate immune properties in comparison with total peripheral blood CD19+ cells.

Robust dimethyl-based multiplex-DIA doubles single-cell proteome depth via a reference channel

Single-cell proteomics aims to characterize biological function and heterogeneity at the level of proteins in an unbiased manner. It is currently limited in proteomic depth, throughput, and robustness, which we address here by a streamlined multiplexed workflow using data-independent acquisition (mDIA). We demonstrate automated and complete dimethyl labeling of bulk or single-cell samples, without losing proteomic depth. Lys-N digestion enables five-plex quantification at MS1 and MS2 level. Because the multiplexed channels are quantitatively isolated from each other, mDIA accommodates a reference channel that does not interfere with the target channels. Our algorithm RefQuant takes advantage of this and confidently quantifies twice as many proteins per single cell compared to our previous work (Brunner et al, PMID 35226415), while our workflow currently allows routine analysis of 80 single cells per day. Finally, we combined mDIA with spatial proteomics to increase the throughput of Deep Visual Proteomics seven-fold for microdissection and four-fold for MS analysis. Applying this to primary cutaneous melanoma, we discovered proteomic signatures of cells within distinct tumor microenvironments, showcasing its potential for precision oncology.

Homeostatic role of B-1 cells in tissue immunity

To date, studies of tissue-resident immunity have mainly focused on innate immune cells and T cells, with limited data on B cells. B-1 B cells are a unique subset of B cells with innate-like properties, enriched in murine pleural and peritoneal cavities and distinct from conventional B-2 cells in their ontogeny, phenotype and function. Here we discuss how B-1 cells represent exemplar tissue-resident immune cells, summarizing the evidence for their long-term persistence & self-renewal within tissues, differential transcriptional programming shaped by organ-specific environmental cues, as well as their tissue-homeostatic functions. Finally, we review the emerging data supporting the presence and homeostatic role of B-1 cells across non-lymphoid organs (NLOs) both in mouse and human.

Single-cell reference mapping to construct and extend cell-type hierarchies

Single-cell genomics is now producing an ever-increasing amount of datasets that, when integrated, could provide large-scale reference atlases of tissue in health and disease. Such large-scale atlases increase the scale and generalizability of analyses and enable combining knowledge generated by individual studies. Specifically, individual studies often differ regarding cell annotation terminology and depth, with different groups specializing in different cell type compartments, often using distinct terminology. Understanding how these distinct sets of annotations are related and complement each other would mark a major step towards a consensus-based cell-type annotation reflecting the latest knowledge in the field. Whereas recent computational techniques, referred to as 'reference mapping' methods, facilitate the usage and expansion of existing reference atlases by mapping new datasets (i.e. queries) onto an atlas; a systematic approach towards harmonizing dataset-specific cell-type terminology and annotation depth is still lacking. Here, we present 'treeArches', a framework to automatically build and extend reference atlases while enriching them with an updatable hierarchy of cell-type annotations across different datasets. We demonstrate various use cases for treeArches, from automatically resolving relations between reference and query cell types to identifying unseen cell types absent in the reference, such as disease-associated cell states. We envision treeArches enabling data-driven construction of consensus atlas-level cell-type hierarchies and facilitating efficient usage of reference atlases.

A novel cryopreservation and biobanking strategy to study lymphoid tissue stromal cells in human disease

Nonhematopoietic lymph node stromal cells (LNSCs) regulate lymphocyte trafficking, survival, and function for key roles in host defense, autoimmunity, alloimmunity, and lymphoproliferative disorders. However, the study of LNSCs in human diseases is complicated by a dependence on viable lymphoid tissues, which are most often excised prior to establishment of a specific diagnosis. Here, we demonstrate that cryopreservation can be used to bank lymphoid tissue for the study of LNSCs in human disease. Using human tonsils and lymph nodes (LN), lymphoid tissue fragments were cryopreserved for subsequent enzymatic digestion and recovery of viable nonhematopoietic cells. Flow cytometry and single-cell transcriptomics identified comparable proportions of LN stromal cell types in fresh and cryopreserved tissue. Moreover, cryopreservation had little effect on transcriptional profiles, which showed significant overlap between tonsils and LN. The presence and spatial distribution of transcriptionally defined cell types were confirmed by in situ analyses. Our broadly applicable approach promises to greatly enable research into the roles of LNSCs in human disease.

Tissue-specific macrophages: how they develop and choreograph tissue biology

Macrophages are innate immune cells that form a 3D network in all our tissues, where they phagocytose dying cells and cell debris, immune complexes, bacteria and other waste products. Simultaneously, they produce growth factors and signalling molecules - such activities not only promote host protection in response to invading microorganisms but are also crucial for organ development and homeostasis. There is mounting evidence of macrophages orchestrating fundamental physiological processes, such as blood vessel formation, adipogenesis, metabolism and central and peripheral neuronal function. In parallel, novel methodologies have led to the characterization of tissue-specific macrophages, with distinct subpopulations of these cells showing different developmental trajectories, transcriptional programmes and life cycles. Here, we summarize our growing knowledge of macrophage diversity and how macrophage subsets orchestrate tissue development and function. We further interrelate macrophage ontogeny with their core functions across tissues, that is, the signalling events within the macrophage niche that may control organ functionality during development, homeostasis and ageing. Finally, we highlight the open questions that will need to be addressed by future studies to better understand the tissue-specific functions of distinct macrophage subsets.

Intercellular cross-talk through lineage-specific gap junction of cancer-associated fibroblasts related to stromal fibrosis and prognosis

Stromal fibrosis in cancer is usually associated with poor prognosis and chemotherapy resistance. It is thought to be caused by fibroblasts; however, the exact mechanism is not yet well understood. The study aimed to identify lineage-specific cancer-associated fibroblast (CAF) subgroup and their associations with extracellular matrix remodeling and clinical significances in various tumor types using single-cell and bulk RNA sequencing data. Through unsupervised clustering, six subclusters of CAFs were identified, including a cluster with exclusively high gap junction protein beta-2 (GJB2) expression. This cluster was named GJB2-positive CAF. It was found to be a unique subgroup of terminally differentiated CAFs associated with collagen gene expression and extracellular matrix remodeling. GJB2-positive CAFs showed higher communication frequency with vascular endothelial cells and cancer cells than GJB2-negative CAFs. Moreover, GJB2 was poorly expressed in normal tissues, indicating that its expression is dependent on interaction with other cells, including vascular endothelial cells and cancer cells. Finally, the study investigated the clinical significance of GJB2 signature score for GJB2-positive CAFs in cancer and found a correlation with poor prognosis. These results suggest that GJB2-positive CAF is a unique fibroblast subtype involved in extracellular matrix remodeling, with significant clinical implications in cancer.

Yolk sac cell atlas reveals multiorgan functions during human early development

The extraembryonic yolk sac (YS) ensures delivery of nutritional support and oxygen to the developing embryo but remains ill-defined in humans. We therefore assembled a comprehensive multiomic reference of the human YS from 3 to 8 postconception weeks by integrating single-cell protein and gene expression data. Beyond its recognized role as a site of hematopoiesis, we highlight roles in metabolism, coagulation, vascular development, and hematopoietic regulation. We reconstructed the emergence and decline of YS hematopoietic stem and progenitor cells from hemogenic endothelium and revealed a YS-specific accelerated route to macrophage production that seeds developing organs. The multiorgan functions of the YS are superseded as intraembryonic organs develop, effecting a multifaceted relay of vital functions as pregnancy proceeds.