Single-cell RNA-sequencing uncovers transcriptional states and fate decisions in haematopoiesis

Diversity and functional specialization of oyster immune cells uncovered by integrative single-cell level investigations

Mollusks are a major component of animal biodiversity and play a critical role in ecosystems and global food security. The Pacific oyster, Crassostrea (Magallana) gigas, is the most farmed bivalve mollusk in the world and is becoming a model species for invertebrate biology. Despite the extensive research on hemocytes, the immune cells of bivalves, their characterization remains elusive. Here, we were able to extensively characterize the diverse hemocytes and identified at least seven functionally distinct cell types and three hematopoietic lineages. A combination of single-cell RNA sequencing, quantitative cytology, cell sorting, functional assays, and pseudo-time analyses was used to deliver a comprehensive view of the distinct hemocyte types. This integrative analysis enabled us to reconcile molecular and cellular data and identify distinct cell types performing specialized immune functions, such as phagocytosis, reactive oxygen species production, copper accumulation, and expression of antimicrobial peptides. This study emphasized the need for more in depth studies of cellular immunity in mollusks and non-model invertebrates and set the ground for further comparative immunology studies at the cellular level.

Self-Supervised Graph Representation Learning for Single-Cell Classification

Accurately identifying cell types in single-cell RNA sequencing data is critical for understanding cellular differentiation and pathological mechanisms in downstream analysis. As traditional biological approaches are laborious and time-intensive, it is imperative to develop computational biology methods for cell classification. However, it remains a challenge for existing methods to adequately utilize the potential gene expression information within the vast amount of unlabeled cell data, which limits their classification and generalization performance. Therefore, we propose a novel self-supervised graph representation learning framework for single-cell classification, named scSSGC. Specifically, in the pre-training stage of self-supervised learning, multiple K-means clustering tasks conducted on unlabeled cell data are jointly employed for model training, thereby mitigating the issue of limited labeled data. To effectively capture the potential interactions among cells, we introduce a locally augmented graph neural network to enhance the information aggregation capability for nodes with fewer neighbors in the cell graph. A range of benchmark experiments demonstrates that scSSGC outperforms existing state-of-the-art cell classification methods. More importantly, scSSGC provides stable performance when faced with cross-datasets, indicating better generalization ability.

scVAEDer: integrating deep diffusion models and variational autoencoders for single-cell transcriptomics analysis

Discovering a lower-dimensional embedding of single-cell data can improve downstream analysis. The embedding should encapsulate both the high-level features and low-level variations. While existing generative models attempt to learn such low-dimensional representations, they have limitations. Here, we introduce scVAEDer, a scalable deep-learning model that combines the power of variational autoencoders and deep diffusion models to learn a meaningful representation that retains both global structure and local variations. Using the learned embeddings, scVAEDer can generate novel scRNA-seq data, predict perturbation response on various cell types, identify changes in gene expression during dedifferentiation, and detect master regulators in biological processes.

scPerb: Predict single-cell perturbation via style transfer-based variational autoencoder

INTRODUCTION

Traditional methods for obtaining cellular responses after perturbation are usually labor-intensive and costly, especially when working with multiple different experimental conditions. Therefore, accurate prediction of cellular responses to perturbations is of great importance in computational biology. Existing methodologies, such as graph-based approaches, vector arithmetic, and neural networks, either mix perturbation-related variances with cell-type-specific patterns or implicitly distinguish them within black-box models.

OBJECTIVES

This study aims to introduce and demonstrate a novel framework, scPerb, which explicitly extracts perturbation-related variances and transfers them from unperturbed to perturbed cells to accurately predict the effect of perturbation in single-cell level.

METHODS

scPerb utilizes a style transfer strategy by incorporating a style encoder into the architecture of a variational autoencoder. The style encoder captures the differences in latent representations between unperturbed and perturbed cells, enabling accurate prediction of post-perturbation gene expression data.

RESULTS

Comprehensive comparisons with existing methods demonstrate that scPerb delivers improved performance and higher accuracy in predicting cellular responses to perturbations. Notably, scPerb outperforms other methods across multiple datasets, achieving superior R2 values of 0.98, 0.98, and 0.96 on three benchmarking datasets.

CONCLUSION

scPerb offers a significant advancement in predicting cellular responses by effectively separating and transferring perturbation-related variances. This framework not only enhances prediction accuracy but also provides a robust tool for computational biology, addressing the limitations of current methodologies.

Single-cell Transcriptional Landscape of Temporal Neutrophil Response to Burn Wound in Larval Zebrafish

Neutrophils accumulate early in tissue injury. However, the cellular and functional heterogeneity of neutrophils during homeostasis and in response to tissue damage remains unclear. In this study, we use larval zebrafish to understand neutrophil responses to thermal injury. Single-cell transcriptional mapping of myeloid cells during a 3-d time course in burn and control larvae revealed distinct neutrophil subsets and their cell-cell interactions with macrophages across time and conditions. The trajectory formed by three zebrafish neutrophil subsets resembles human neutrophil maturation, with varying transition patterns between conditions. Through ligand-receptor cell-cell interaction analysis, we found that neutrophils communicate more in burns in a pathway and temporal manner. Finally, we identified the correlation between zebrafish myeloid signatures and human burn severity, establishing GPR84+ neutrophils as a potential marker of early innate immune response in burns. This work builds a comparative single-cell transcriptomic framework to identify neutrophil markers of tissue damage using model organisms.

A JAGN1-associated severe congenital neutropenia zebrafish model revealed an altered G-CSFR signaling and UPR activation

ABSTRACT

A variety of autosomal recessive mutations in the JAGN1 gene cause severe congenital neutropenia (CN). However, the underlying pathomechanism remains poorly understood, mainly because of the limited availability of primary hematopoietic stem cells from JAGN1-CN patients and the absence of animal models. In this study, we aimed to address these limitations by establishing a zebrafish model of JAGN1-CN. We found 2 paralogs of the human JAGN1 gene, namely jagn1a and jagn1b, which play distinct roles during zebrafish hematopoiesis. Using various approaches such as morpholino-based knockdown, CRISPR/Cas9-based gene editing, and misexpression of a jagn1b harboring a specific human mutation, we successfully developed neutropenia while leaving other hematopoietic lineages unaffected. Further analysis of our model revealed significant upregulation of apoptosis and genes involved in the unfolded protein response (UPR). However, neither UPR nor apoptosis is the primary mechanism that leads to neutropenia in zebrafish. Instead, Jagn1b has a critical role in granulocyte colony-stimulating factor receptor signaling and steady-state granulopoiesis, shedding light on the pathogenesis of neutropenia associated with JAGN1 mutations. The establishment of a zebrafish model for JAGN1-CN represents a significant advancement in understanding the specific pathologic pathways underlying the disease. This model provides a valuable in vivo tool for further investigation and exploration of potential therapeutic strategies.

GATA2 heterozygosity causes an epigenetic feedback mechanism resulting in myeloid and erythroid dysplasia

The transcription factor GATA2 has a pivotal role in haematopoiesis. Heterozygous germline GATA2 mutations result in a syndrome characterized by immunodeficiency, bone marrow failure and predispositions to myelodysplastic syndrome (MDS) and acute myeloid leukaemia. Clinical symptoms in these patients are diverse and mechanisms driving GATA2-related phenotypes are largely unknown. To explore the impact of GATA2 haploinsufficiency on haematopoiesis, we generated a zebrafish model carrying a heterozygous mutation of gata2b (gata2b+/-), an orthologue of GATA2. Morphological analysis revealed myeloid and erythroid dysplasia in gata2b+/- kidney marrow. Because Gata2b could affect both transcription and chromatin accessibility during lineage differentiation, this was assessed by single-cell (sc) RNA-seq and single-nucleus (sn) ATAC-seq. Sn-ATAC-seq showed that the co-accessibility between the transcription start site (TSS) and a -3.5-4.1 kb putative enhancer was more robust in gata2b+/- zebrafish HSPCs compared to wild type, increasing gata2b expression and resulting in higher genome-wide Gata2b motif use in HSPCs. As a result of increased accessibility of the gata2b locus, gata2b+/- chromatin was also more accessible during lineage differentiation. scRNA-seq data revealed myeloid differentiation defects, that is, impaired cell cycle progression, reduced expression of cebpa and cebpb and increased signatures of ribosome biogenesis. These data also revealed a differentiation delay in erythroid progenitors, aberrant proliferative signatures and down-regulation of Gata1a, a master regulator of erythropoiesis, which worsened with age. These findings suggest that cell-intrinsic compensatory mechanisms, needed to obtain normal levels of Gata2b in heterozygous HSPCs to maintain their integrity, result in aberrant lineage differentiation, thereby representing a critical step in the predisposition to MDS.

Fatecode enables cell fate regulator prediction using classification-supervised autoencoder perturbation

Cell reprogramming, which guides the conversion between cell states, is a promising technology for tissue repair and regeneration, with the ultimate goal of accelerating recovery from diseases or injuries. To accomplish this, regulators must be identified and manipulated to control cell fate. We propose Fatecode, a computational method that predicts cell fate regulators based only on single-cell RNA sequencing (scRNA-seq) data. Fatecode learns a latent representation of the scRNA-seq data using a deep learning-based classification-supervised autoencoder and then performs in silico perturbation experiments on the latent representation to predict genes that, when perturbed, would alter the original cell type distribution to increase or decrease the population size of a cell type of interest. We assessed Fatecode's performance using simulations from a mechanistic gene-regulatory network model and scRNA-seq data mapping blood and brain development of different organisms. Our results suggest that Fatecode can detect known cell fate regulators from single-cell transcriptomics datasets.

Comprehensive transcriptional atlas of human adenomyosis deciphered by the integration of single-cell RNA-sequencing and spatial transcriptomics

Adenomyosis is a poorly understood gynecological disorder lacking effective treatments. Controversy persists regarding "invagination" and "metaplasia" theories. The endometrial-myometrial junction (EMJ) connects the endometrium and myometrium and is important for diagnosing and classifying adenomyosis, but its in-depth study is just beginning. Using single-cell RNA sequencing and spatial profiling, we mapped transcriptional alterations across eutopic endometrium, lesions, and EMJ. Within lesions, we identified unique epithelial (LGR5+) and invasive stromal (PKIB+) subpopulations, along with WFDC1+ progenitor cells, supporting a complex interplay between "invagination" and "metaplasia" theories of pathogenesis. Further, we observed endothelial cell heterogeneity and abnormal angiogenic signaling involving vascular endothelial growth factor and angiopoietin pathways. Cell-cell communication differed markedly between ectopic and eutopic endometrium, with aberrant signaling in lesions involving pleiotrophin, TWEAK, and WNT cascades. This study reveals unique stem cell-like and invasive cell subpopulations within adenomyosis lesions identified, dysfunctional signaling, and EMJ abnormalities critical to developing precise diagnostic and therapeutic strategies.

Modeling nontuberculous mycobacterial infections in zebrafish

The incidence of infections due to nontuberculous mycobacteria (NTM) has increased rapidly in recent years, surpassing tuberculosis in developed countries. Due to inherent antimicrobial resistance, NTM infections are particularly difficult to treat with low cure rates. There is an urgent need to understand NTM pathogenesis and to develop novel therapeutic approaches for the treatment of NTM diseases. Zebrafish have emerged as an excellent animal model due to genetic amenability and optical transparency during embryonic development, allowing spatiotemporal visualization of host-pathogen interactions. Furthermore, adult zebrafish possess fully functional innate and adaptive immunity and recapitulate important pathophysiological hallmarks of mycobacterial infection. Here, we report recent breakthroughs in understanding the hallmarks of NTM infections using the zebrafish model.

Computational single-cell methods for predicting cancer risk

Despite recent biotechnological breakthroughs, cancer risk prediction remains a formidable computational and experimental challenge. Addressing it is critical in order to improve prevention, early detection and survival rates. Here, I briefly summarize some key emerging theoretical and computational challenges as well as recent computational advances that promise to help realize the goals of cancer-risk prediction. The focus is on computational strategies based on single-cell data, in particular on bottom-up network modeling approaches that aim to estimate cancer stemness and dedifferentiation at single-cell resolution from a systems-biological perspective. I will describe two promising methods, a tissue and cell-lineage independent one based on the concept of diffusion network entropy, and a tissue and cell-lineage specific one that uses transcription factor regulons. Application of these tools to single-cell and single-nucleus RNA-seq data from stages prior to invasive cancer reveal that they can successfully delineate the heterogeneous inter-cellular cancer-risk landscape, identifying those cells that are more likely to turn cancerous. Bottom-up systems biological modeling of single-cell omic data is a novel computational analysis paradigm that promises to facilitate the development of preventive, early detection and cancer-risk prediction strategies.

Tribbles1 is host protective during in vivo mycobacterial infection

Tuberculosis is a major global health problem and is one of the top 10 causes of death worldwide. There is a pressing need for new treatments that circumvent emerging antibiotic resistance. Mycobacterium tuberculosis parasitises macrophages, reprogramming them to establish a niche in which to proliferate, therefore macrophage manipulation is a potential host-directed therapy if druggable molecular targets could be identified. The pseudokinase Tribbles1 (Trib1) regulates multiple innate immune processes and inflammatory profiles making it a potential drug target in infections. Trib1 controls macrophage function, cytokine production, and macrophage polarisation. Despite wide-ranging effects on leukocyte biology, data exploring the roles of Tribbles in infection in vivo are limited. Here, we identify that human Tribbles1 is expressed in monocytes and is upregulated at the transcript level after stimulation with mycobacterial antigen. To investigate the mechanistic roles of Tribbles in the host response to mycobacteria in vivo, we used a zebrafish Mycobacterium marinum (Mm) infection tuberculosis model. Zebrafish Tribbles family members were characterised and shown to have substantial mRNA and protein sequence homology to their human orthologues. trib1 overexpression was host-protective against Mm infection, reducing burden by approximately 50%. Conversely, trib1 knockdown/knockout exhibited increased infection. Mechanistically, trib1 overexpression significantly increased the levels of proinflammatory factors il-1β and nitric oxide. The host-protective effect of trib1 was found to be dependent on the E3 ubiquitin kinase Cop1. These findings highlight the importance of Trib1 and Cop1 as immune regulators during infection in vivo and suggest that enhancing macrophage TRIB1 levels may provide a tractable therapeutic intervention to improve bacterial infection outcomes in tuberculosis.

A nox2/cybb zebrafish mutant with defective myeloid cell reactive oxygen species production displays normal initial neutrophil recruitment to sterile tail injuries

Reactive oxygen species are important effectors and modifiers of the acute inflammatory response, recruiting phagocytes including neutrophils to sites of tissue injury. In turn, phagocytes such as neutrophils are both consumers and producers of reactive oxygen species. Phagocytes including neutrophils generate reactive oxygen species in an oxidative burst through the activity of a multimeric phagocytic nicotinamide adenine dinucleotide phosphate oxidase complex. Mutations in the NOX2/CYBB (previously gp91phox) nicotinamide adenine dinucleotide phosphate oxidase subunit are the commonest cause of chronic granulomatous disease, a disease characterized by infection susceptibility and an inflammatory phenotype. To model chronic granulomatous disease, we made a nox2/cybb zebrafish (Danio rerio) mutant and demonstrated it to have severely impaired myeloid cell reactive oxygen species production. Reduced early survival of nox2 mutant embryos indicated an essential requirement for nox2 during early development. In nox2/cybb zebrafish mutants, the dynamics of initial neutrophil recruitment to both mild and severe surgical tailfin wounds was normal, suggesting that excessive neutrophil recruitment at the initiation of inflammation is not the primary cause of the "sterile" inflammatory phenotype of chronic granulomatous disease patients. This nox2 zebrafish mutant adds to existing in vivo models for studying reactive oxygen species function in myeloid cells including neutrophils in development and disease.

Ly6Chi Monocytes Are Metabolically Reprogrammed in the Blood during Inflammatory Stimulation and Require Intact OxPhos for Chemotaxis and Monocyte to Macrophage Differentiation

Acute inflammation is a rapid and dynamic process involving the recruitment and activation of multiple cell types in a coordinated and precise manner. Here, we investigate the origin and transcriptional reprogramming of monocytes using a model of acute inflammation, zymosan-induced peritonitis. Monocyte trafficking and adoptive transfer experiments confirmed that monocytes undergo rapid phenotypic change as they exit the blood and give rise to monocyte-derived macrophages that persist during the resolution of inflammation. Single-cell transcriptomics revealed significant heterogeneity within the surface marker-defined CD11b+Ly6G-Ly6Chi monocyte populations within the blood and at the site of inflammation. We show that two major transcriptional reprogramming events occur during the initial six hours of Ly6Chi monocyte mobilisation, one in the blood priming monocytes for migration and a second at the site of inflammation. Pathway analysis revealed an important role for oxidative phosphorylation (OxPhos) during both these reprogramming events. Experimentally, we demonstrate that OxPhos via the intact mitochondrial electron transport chain is essential for murine and human monocyte chemotaxis. Moreover, OxPhos is needed for monocyte-to-macrophage differentiation and macrophage M(IL-4) polarisation. These new findings from transcriptional profiling open up the possibility that shifting monocyte metabolic capacity towards OxPhos could facilitate enhanced macrophage M2-like polarisation to aid inflammation resolution and tissue repair.

PhyloVelo enhances transcriptomic velocity field mapping using monotonically expressed genes

Single-cell RNA sequencing (scRNA-seq) is a powerful approach for studying cellular differentiation, but accurately tracking cell fate transitions can be challenging, especially in disease conditions. Here we introduce PhyloVelo, a computational framework that estimates the velocity of transcriptomic dynamics by using monotonically expressed genes (MEGs) or genes with expression patterns that either increase or decrease, but do not cycle, through phylogenetic time. Through integration of scRNA-seq data with lineage information, PhyloVelo identifies MEGs and reconstructs a transcriptomic velocity field. We validate PhyloVelo using simulated data and Caenorhabditis elegans ground truth data, successfully recovering linear, bifurcated and convergent differentiations. Applying PhyloVelo to seven lineage-traced scRNA-seq datasets, generated using CRISPR-Cas9 editing, lentiviral barcoding or immune repertoire profiling, demonstrates its high accuracy and robustness in inferring complex lineage trajectories while outperforming RNA velocity. Additionally, we discovered that MEGs across tissues and organisms share similar functions in translation and ribosome biogenesis.

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.

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.

Cell atlas of the Atlantic salmon spleen reveals immune cell heterogeneity and cell-specific responses to bacterial infection

The spleen is a conserved secondary lymphoid organ that emerged in parallel to adaptive immunity in early jawed vertebrates. Recent studies have applied single cell transcriptomics to reveal the cellular composition of spleen in several species, cataloguing diverse immune cell types and subpopulations. In this study, 51,119 spleen nuclei transcriptomes were comprehensively investigated in the commercially important teleost Atlantic salmon (Salmo salar L.), contrasting control animals with those challenged with the bacterial pathogen Aeromonas salmonicida. We identified clusters of nuclei representing the expected major cell types, namely T cells, B cells, natural killer-like cells, granulocytes, mononuclear phagocytes, endothelial cells, mesenchymal cells, erythrocytes and thrombocytes. We discovered heterogeneity within several immune lineages, providing evidence for resident macrophages and melanomacrophages, infiltrating monocytes, several candidate dendritic cell subpopulations, and B cells at distinct stages of differentiation, including plasma cells and an igt + subset. We provide evidence for twelve candidate T cell subsets, including cd4+ T helper and regulatory T cells, one cd8+ subset, three γδT subsets, and populations double negative for cd4 and cd8. The number of genes showing differential expression during the early stages of Aeromonas infection was highly variable across immune cell types, with the largest changes observed in macrophages and infiltrating monocytes, followed by resting mature B cells. Our analysis provides evidence for a local inflammatory response to infection alongside B cell maturation in the spleen, and upregulation of ccr9 genes in igt + B cells, T helper and cd8+ cells, and monocytes, consistent with the recruitment of immune cell populations to the gut to deal with Aeromonas infection. Overall, this study provides a new cell-resolved perspective of the immune actions of Atlantic salmon spleen, highlighting extensive heterogeneity hidden to bulk transcriptomics. We further provide a large catalogue of cell-specific marker genes that can be leveraged to further explore the function and structural organization of the salmonid immune system.

A single-cell atlas of conventional central chondrosarcoma reveals the role of endoplasmic reticulum stress in malignant transformation

The transformation of benign lesions to malignant tumours is a crucial aspect of understanding chondrosarcomas, which are malignant cartilage tumours that could develop from benign chondroid lesions. However, the process of malignant transformation for chondroid lesions remains poorly understood, and no reliable markers are available to aid clinical decision-making. To address this issue, we conducted a study analysing 11 primary cartilage tumours and controls using single-cell RNA sequencing. By creating a single-cell atlas, we were able to identify the role of endoplasmic reticulum (ER) stress in the malignant transformation of conventional central chondrosarcomas (CCCS). Our research revealed that lower levels of ER stress promote chondrosarcoma growth in a patient-derived xenograft mouse model, while intensive ER stress reduces primary chondrosarcoma cell viability. Furthermore, we discovered that the NF-κB pathway alleviates ER stress-induced apoptosis during chondrosarcoma progression. Our single-cell signatures and large public data support the use of key ER stress regulators, such as DNA Damage Inducible Transcript 3 (DDIT3; also known as CHOP), as malignant markers for overall patient survival. Ultimately, our study highlights the significant role that ER stress plays in the malignant transformation of cartilaginous tumours and provides a valuable resource for future diagnostic markers and therapeutic strategies.

Fishing Innate Immune System Properties through the Transcriptomic Single-Cell Data of Teleostei

The innate immune system is the first line of defense in multicellular organisms. Danio rerio is widely considered a promising model for IIS-related research, with the most amount of scRNAseq data available among Teleostei. We summarized the scRNAseq and spatial transcriptomics experiments related to the IIS for zebrafish and other Teleostei from the GEO NCBI and the Single-Cell Expression Atlas. We found a considerable number of scRNAseq experiments at different stages of zebrafish development in organs such as the kidney, liver, stomach, heart, and brain. These datasets could be further used to conduct large-scale meta-analyses and to compare the IIS of zebrafish with the mammalian one. However, only a small number of scRNAseq datasets are available for other fish (turbot, salmon, cavefish, and dark sleeper). Since fish biology is very diverse, it would be a major mistake to use zebrafish alone in fish immunology studies. In particular, there is a special need for new scRNAseq experiments involving nonmodel Teleostei, e.g., long-lived species, cancer-resistant fish, and various fish ecotypes.

Single-cell and spatial analyses reveal a tradeoff between murine mammary proliferation and lineage programs associated with endocrine cues

Although distinct epithelial cell types have been distinguished in glandular tissues such as the mammary gland, the extent of heterogeneity within each cell type and the degree of endocrine control of this diversity across development are incompletely understood. By combining mass cytometry and cyclic immunofluorescence, we define a rich array of murine mammary epithelial cell subtypes associated with puberty, the estrous cycle, and sex. These subtypes are differentially proliferative and spatially segregate distinctly in adult versus pubescent glands. Further, we identify systematic suppression of lineage programs at the protein and RNA levels as a common feature of mammary epithelial expansion during puberty, the estrous cycle, and gestation and uncover a pervasive enrichment of ribosomal protein genes in luminal cells elicited specifically during progesterone-dominant expansionary periods. Collectively, these data expand our knowledge of murine mammary epithelial heterogeneity and connect endocrine-driven epithelial expansion with lineage suppression.

Widespread sex dimorphism across single-cell transcriptomes of adult African turquoise killifish tissues

The African turquoise killifish (Nothobranchius furzeri), the shortest-lived vertebrate that can be bred in captivity, is an emerging model organism for aging research. Here, we describe a multitissue, single-cell gene expression atlas of female and male blood, kidney, liver, and spleen. We annotate 22 cell types, define marker genes, and infer differentiation trajectories. We find pervasive sex-dimorphic gene expression across cell types. Sex-dimorphic genes tend to be linked to lipid metabolism, consistent with clear differences in lipid storage in female vs. male turquoise killifish livers. We use machine learning to predict sex using single-cell gene expression and identify potential markers for molecular sex identity. As a proof of principle, we show that our atlas can be used to deconvolute existing bulk RNA sequencing (RNA-seq) data to obtain accurate estimates of cell type proportions. This atlas can be a resource to the community that could be leveraged to develop cell-type-specific expression in transgenic animals.

Multi-omics analysis of human mesenchymal stem cells shows cell aging that alters immunomodulatory activity through the downregulation of PD-L1

Mesenchymal stem cells (MSCs) possess potent immunomodulatory activity and have been extensively investigated for their therapeutic potential in treating inflammatory disorders. However, the mechanisms underlying the immunosuppressive function of MSCs are not fully understood, hindering the development of standardized MSC-based therapies for clinical use. In this study, we profile the single-cell transcriptomes of MSCs isolated from adipose tissue (AD), bone marrow (BM), placental chorionic membrane (PM), and umbilical cord (UC). Our results demonstrate that MSCs undergo a progressive aging process and that the cellular senescence state influences their immunosuppressive activity by downregulating PD-L1 expression. Through integrated analysis of single-cell transcriptomic and proteomic data, we identify GATA2 as a regulator of MSC senescence and PD-L1 expression. Overall, our findings highlight the roles of cell aging and PD-L1 expression in modulating the immunosuppressive efficacy of MSCs and implicating perinatal MSC therapy for clinical applications in inflammatory disorders.

Widespread sex-dimorphism across single-cell transcriptomes of adult African turquoise killifish tissues

The African turquoise killifish (Nothobranchius furzeri), the shortest-lived vertebrate that can be bred in captivity, is an emerging model organism to study vertebrate aging. Here we describe the first multi-tissue, single-cell gene expression atlas of female and male turquoise killifish tissues comprising immune and metabolic cells from the blood, kidney, liver, and spleen. We were able to annotate 22 distinct cell types, define associated marker genes, and infer differentiation trajectories. Using this dataset, we found pervasive sex-dimorphic gene expression across cell types, especially in the liver. Sex-dimorphic genes tended to be involved in processes related to lipid metabolism, and indeed, we observed clear differences in lipid storage in female vs. male turquoise killifish livers. Importantly, we use machine-learning to predict sex using single-cell gene expression in our atlas and identify potential transcriptional markers for molecular sex identity in this species. As proof-of-principle, we show that our atlas can be used to deconvolute existing liver bulk RNA-seq data in this species to obtain accurate estimates of cell type proportions across biological conditions. We believe that this single-cell atlas can be a resource to the community that could notably be leveraged to identify cell type-specific genes for cell type-specific expression in transgenic animals.

Tm4sf1-marked Endothelial Subpopulation Is Dysregulated in Pulmonary Arterial Hypertension

The identification and role of endothelial progenitor cells in pulmonary arterial hypertension (PAH) remain controversial. Single-cell omics analysis can shed light on endothelial progenitor cells and their potential contribution to PAH pathobiology. We aim to identify endothelial cells that may have stem/progenitor potential in rat lungs and assess their relevance to PAH. Differential expression, gene set enrichment, cell-cell communication, and trajectory reconstruction analyses were performed on lung endothelial cells from single-cell RNA sequencing of Sugen-hypoxia, monocrotaline, and control rats. Relevance to human PAH was assessed in multiple independent blood and lung transcriptomic data sets. Rat lung endothelial cells were visualized by immunofluorescence in situ, analyzed by flow cytometry, and assessed for tubulogenesis in vitro. A subpopulation of endothelial cells (endothelial arterial type 2 [EA2]) marked by Tm4sf1 (transmembrane 4 L six family member 1), a gene strongly implicated in cancer, harbored a distinct transcriptomic signature enriched for angiogenesis and CXCL12 signaling. Trajectory analysis predicted that EA2 has a less differentiated state compared with other endothelial subpopulations. Analysis of independent data sets revealed that TM4SF1 is downregulated in lungs and endothelial cells from patients and PAH models, is a marker for hematopoietic stem cells, and is upregulated in PAH circulation. TM4SF1+CD31+ rat lung endothelial cells were visualized in distal pulmonary arteries, expressed hematopoietic marker CD45, and formed tubules in coculture with lung fibroblasts. Our study uncovered a novel Tm4sf1-marked subpopulation of rat lung endothelial cells that may have stem/progenitor potential and demonstrated its relevance to PAH. Future studies are warranted to further elucidate the role of EA2 and Tm4sf1 in PAH.

Activated PI3K delta syndrome 1 mutations cause neutrophilia in zebrafish larvae

People with activated PI3 kinase delta syndrome 1 (APDS1) suffer from immune deficiency and severe bronchiectasis. APDS1 is caused by dominant activating mutations of the PIK3CD gene that encodes the PI3 kinase delta (PI3Kδ) catalytic subunit. Despite the importance of innate immunity defects in bronchiectasis, there has been limited investigation of neutrophils or macrophages in APDS1 patients or mouse models. Zebrafish embryos provide an ideal system to study neutrophils and macrophages. We used CRISPR-Cas9 and CRISPR-Cpf1, with oligonucleotide-directed homologous repair, to engineer zebrafish equivalents of the two most prevalent human APDS1 disease mutations. These zebrafish pik3cd alleles dominantly caused excessive neutrophilic inflammation in a tail-fin injury model. They also resulted in total body neutrophilia in the absence of any inflammatory stimulus but normal numbers of macrophages. Exposure of zebrafish to the PI3Kδ inhibitor CAL-101 reversed the total body neutrophilia. There was no apparent defect in neutrophil maturation or migration, and tail-fin regeneration was unimpaired. Overall, the finding is of enhanced granulopoeisis, in the absence of notable phenotypic change in neutrophils and macrophages.

Transgenic IDH2R172K and IDH2R140Q zebrafish models recapitulated features of human acute myeloid leukemia

Isocitrate dehydrogenase 2 (IDH2) mutations occur in more than 15% of cytogenetically normal acute myeloid leukemia (CN-AML) but comparative studies of their roles in leukemogenesis have been scarce. We generated zebrafish models of IDH2^R172K and IDH2^R140Q AML and reported their pathologic, functional and transcriptomic features and therapeutic responses to target therapies. Transgenic embryos co-expressing FLT3^ITD and IDH2 mutations showed accentuation of myelopoiesis. As these embryos were raised to adulthood, full-blown leukemia ensued with multi-lineage dysplasia, increase in myeloblasts and marrow cellularity and splenomegaly. The leukemia cells were transplantable into primary and secondary recipients and resulted in more aggressive disease. Tg(Runx1:FLT3^ITDIDH2^R172K) but not Tg(Runx1:FLT3^ITDIDH2^R140Q) zebrafish showed an increase in T-cell development at embryonic and adult stages. Single-cell transcriptomic analysis revealed increased myeloid skewing, differentiation blockade and enrichment of leukemia-associated gene signatures in both zebrafish models. Tg(Runx1:FLT3^ITDIDH2^R172K) but not Tg(Runx1:FLT3^ITDIDH2^R140Q) zebrafish showed an increase in interferon signals at the adult stage. Leukemic phenotypes in both zebrafish could be ameliorated by quizartinib and enasidenib. In conclusion, the zebrafish models of IDH2 mutated AML recapitulated the morphologic, clinical, functional and transcriptomic characteristics of human diseases, and provided the prototype for developing zebrafish leukemia models of other genotypes that would become a platform for high throughput drug screening.

Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression

Single-cell RNA sequencing studies have suggested that total mRNA content correlates with tumor phenotypes. Technical and analytical challenges, however, have so far impeded at-scale pan-cancer examination of total mRNA content. Here we present a method to quantify tumor-specific total mRNA expression (TmS) from bulk sequencing data, taking into account tumor transcript proportion, purity and ploidy, which are estimated through transcriptomic/genomic deconvolution. We estimate and validate TmS in 6,590 patient tumors across 15 cancer types, identifying significant inter-tumor variability. Across cancers, high TmS is associated with increased risk of disease progression and death. TmS is influenced by cancer-specific patterns of gene alteration and intra-tumor genetic heterogeneity as well as by pan-cancer trends in metabolic dysregulation. Taken together, our results indicate that measuring cell-type-specific total mRNA expression in tumor cells predicts tumor phenotypes and clinical outcomes.

Single-cell RNA sequencing analysis of T helper cell differentiation and heterogeneity

Single-cell transcriptomics has emerged as a powerful tool to investigate cells' biological landscape and focus on the expression profile of individual cells. Major advantage of this approach is an analysis of highly complex and heterogeneous cell populations, such as a specific subpopulation of T helper cells that are known to differentiate into distinct subpopulations. The need for distinguishing the specific expression profile is even more important considering the T cell plasticity. However, importantly, the universal pipelines for single-cell analysis are usually not sufficient for every cell type. Here, the aims are to analyze the diversity of T cell phenotypes employing classical in vitro cytokine-mediated differentiation of human T cells isolated from human peripheral blood by single-cell transcriptomic approach with support of labelled antibodies and a comprehensive bioinformatics analysis using combination of Seurat, Nebulosa, GGplot and others. The results showed high expression similarities between Th1 and Th17 phenotype and very distinct Th2 expression profile. In a case of Th2 highly specific marker genes SPINT2, TRIB3 and CST7 were expressed. Overall, our results demonstrate how donor difference, Th plasticity and cell cycle influence the expression profiles of distinct T cell populations. The results could help to better understand the importance of each step of the analysis when working with T cell single-cell data and observe the results in a more practical way by using our analyzed datasets.

Uncovering the dynamic effects of DEX treatment on lung cancer by integrating bioinformatic inference and multiscale modeling of scRNA-seq and proteomics data

Lung cancer is one of the leading causes of cancer-related death, with a five-year survival rate of 18%. It is a priority for us to understand the underlying mechanisms affecting lung cancer therapeutics' implementation and effectiveness. In this study, we combine the power of Bioinformatics and Systems Biology to comprehensively uncover functional and signaling pathways of drug treatment using bioinformatics inference and multiscale modeling of both scRNA-seq data and proteomics data. Based on a time series of lung adenocarcinoma derived A549 cells after DEX treatment, we first identified the differentially expressed genes (DEGs) in those lung cancer cells. Through the interrogation of regulatory network of those DEGs, we identified key hub genes including TGFβ, MYC, and SMAD3 varied underlie DEX treatment. Further gene set enrichment analysis revealed the TGFβ signaling pathway as the top enriched term. Those genes involved in the TGFβ pathway and their crosstalk with the ERBB pathway presented a strong survival prognosis in clinical lung cancer samples. With the basis of biological validation and literature-based curation, a multiscale model of tumor regulation centered on both TGFβ-induced and ERBB-amplified signaling pathways was developed to characterize the dynamic effects of DEX therapy on lung cancer cells. Our simulation results were well matched to available data of SMAD2, FOXO3, TGFβ1, and TGFβR1 over the time course. Moreover, we provided predictions of different doses to illustrate the trend and therapeutic potential of DEX treatment. The innovative and cross-disciplinary approach can be further applied to other computational studies in tumorigenesis and oncotherapy. We released the approach as a user-friendly tool named BIMM (Bioinformatic Inference and Multiscale Modeling), with all the key features available at https://github.com/chenm19/BIMM.

Single-cell analyses reveal early thymic progenitors and pre-B cells in zebrafish

The zebrafish has proven to be a valuable model organism for studying hematopoiesis, but relatively little is known about zebrafish immune cell development and functional diversity. Elucidating key aspects of zebrafish lymphocyte development and exploring the breadth of effector functions would provide valuable insight into the evolution of adaptive immunity. We performed single-cell RNA sequencing on ∼70,000 cells from the zebrafish marrow and thymus to establish a gene expression map of zebrafish immune cell development. We uncovered rich cellular diversity in the juvenile and adult zebrafish thymus, elucidated B- and T-cell developmental trajectories, and transcriptionally characterized subsets of hematopoietic stem and progenitor cells and early thymic progenitors. Our analysis permitted the identification of two dendritic-like cell populations and provided evidence in support of the existence of a pre-B cell state. Our results provide critical insights into the landscape of zebrafish immunology and offer a foundation for cellular and genetic studies.

SMGR: a joint statistical method for integrative analysis of single-cell multi-omics data

Unravelling the regulatory programs from single-cell multi-omics data has long been one of the major challenges in genomics, especially in the current emerging single-cell field. Currently there is a huge gap between fast-growing single-cell multi-omics data and effective methods for the integrative analysis of these inherent sparse and heterogeneous data. In this study, we have developed a novel method, Single-cell Multi-omics Gene co-Regulatory algorithm (SMGR), to detect coherent functional regulatory signals and target genes from the joint single-cell RNA-sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) data obtained from different samples. Given that scRNA-seq and scATAC-seq data can be captured by zero-inflated Negative Binomial distribution, we utilize a generalized linear regression model to identify the latent representation of consistently expressed genes and peaks, thus enables the identification of co-regulatory programs and the elucidation of regulating mechanisms. Results from both simulation and experimental data demonstrate that SMGR outperforms the existing methods with considerably improved accuracy. To illustrate the biological insights of SMGR, we apply SMGR to mixed-phenotype acute leukemia (MPAL) and identify the MPAL-specific regulatory program with significant peak-gene links, which greatly enhance our understanding of the regulatory mechanisms and potential targets of this complex tumor.

Single-cell gene expression analysis of cryopreserved equine bronchoalveolar cells

The transcriptomic profile of a cell population can now be studied at the cellular level using single-cell mRNA sequencing (scRNA-seq). This novel technique provides the unprecedented opportunity to explore the cellular composition of the bronchoalveolar lavage fluid (BALF) of the horse, a species for which cell type markers are poorly described. Here, scRNA-seq technology was applied to cryopreserved equine BALF cells. Analysis of 4,631 cells isolated from three asthmatic horses in remission identified 16 cell clusters belonging to six major cell types: monocytes/macrophages, T cells, B/plasma cells, dendritic cells, neutrophils and mast cells. Higher resolution analysis of the constituents of the major immune cell populations allowed deep annotation of monocytes/macrophages, T cells and B/plasma cells. A significantly higher lymphocyte/macrophage ratio was detected with scRNA-seq compared to conventional cytological differential cell count. For the first time in horses, we detected a transcriptomic signature consistent with monocyte-lymphocyte complexes. Our findings indicate that scRNA-seq technology is applicable to cryopreserved equine BALF cells, allowing the identification of its major (cytologically differentiated) populations as well as previously unexplored T cell and macrophage subpopulations. Single-cell gene expression analysis has the potential to facilitate understanding of the immunological mechanisms at play in respiratory disorders of the horse, such as equine asthma.

Systematic identification of cell-fate regulatory programs using a single-cell atlas of mouse development

Waddington's epigenetic landscape is a metaphor frequently used to illustrate cell differentiation. Recent advances in single-cell genomics are altering our understanding of the Waddington landscape, yet the molecular mechanisms of cell-fate decisions remain poorly understood. We constructed a cell landscape of mouse lineage differentiation during development at the single-cell level and described both lineage-common and lineage-specific regulatory programs during cell-type maturation. We also found lineage-common regulatory programs that are broadly active during the development of invertebrates and vertebrates. In particular, we identified Xbp1 as an evolutionarily conserved regulator of cell-fate determinations across different species. We demonstrated that Xbp1 transcriptional regulation is important for the stabilization of the gene-regulatory networks for a wide range of mouse cell types. Our results offer genetic and molecular insights into cellular gene-regulatory programs and will serve as a basis for further advancing the understanding of cell-fate decisions.

Hematopoietic Stem and Progenitor Cells (HSPCs) and Hematopoietic Microenvironment: Molecular and Bioinformatic Studies of the Zebrafish Models

Hematopoietic stem cells (HSCs) reside in a specialized microenvironment in a peculiar anatomic location which regulates the maintenance of stem cells and controls its functions. Recent scientific progress in experimental technologies have enabled the specific detection of epigenetic factors responsible for the maintenance and quiescence of the hematopoietic niche, which has improved our knowledge of regulatory mechanisms. The aberrant role of RNA-binding proteins and their impact on the disruption of stem cell biology have been reported by a number of recent studies. Despite recent modernization in hematopoietic microenvironment research avenues, our comprehension of the signaling mechanisms and interactive pathways responsible for integration of the hematopoietic niche is still limited. In the past few decades, zebrafish usage with regards to exploratory studies of the hematopoietic niche has expanded our knowledge for deeper understanding of novel cellular interactions. This review provides an update on the functional roles of different genetic and epigenetic factors and molecular signaling events at different sections of the hematopoietic microenvironment. The explorations of different molecular approaches and interventions of latest web-based tools being used are also outlined. This will help us to get more mechanistic insights and develop therapeutic options for the malignancies.

Ileum tissue single-cell mRNA sequencing elucidates the cellular architecture of pathophysiological changes associated with weaning in piglets

Background

In mammals, transitioning from sole milk uptake to the intake of solid feed results in dramatic developmental changes in intestinal function and immunological status. In fact, weaning stress is often accompanied by intestinal inflammatory processes. To develop effective intervention strategies, it is necessary to characterize the developmental pattern and immune response that occurs on weaning, as we have done in this study for piglets.

Results

To comprehensively delineate cell heterogeneity in ileum tissues and the underlying mechanisms in weaning-induced intestinal inflammation of piglets, we have analyzed the transcriptomes of 42,149 cells from ileum mucosa of normally suckling and post-weaned piglets. There were 31 cell subtypes including epithelial, stromal, and immune cells. A bifurcating trajectory was inferred to separate secretory and absorptive lineages. Integrated cross-species datasets showed well-conserved cellular architectures and transcription signatures between human and pig. Comparative analyses of cellular components, cell–cell communications, and molecular states revealed that T cell subpopulations were significantly altered in weaned piglets. We found that T helper (Th) 17 functional plasticity across changes in the cytokine milieu and the enrichment of granzyme B (GZMB)-expressing cytotoxic T cells potentially exacerbate mucosal inflammation via mitochondrial dysfunction in epithelial cells.

Conclusions

Our work has elucidated the single-cell molecular characteristics of the piglet ileum before and after weaning. We have provided an atlas that portrays the landscape of the intestinal pathophysiological inflammatory process associated with weaning, finding a level of conservation between human and pig that support the use of piglets as a model for human infants.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01321-3.

A human breast atlas integrating single-cell proteomics and transcriptomics

The breast is a dynamic organ whose response to physiological and pathophysiological conditions alters its disease susceptibility, yet the specific effects of these clinical variables on cell state remain poorly annotated. We present a unified, high-resolution breast atlas by integrating single-cell RNA-seq, mass cytometry, and cyclic immunofluorescence, encompassing a myriad of states. We define cell subtypes within the alveolar, hormone-sensing, and basal epithelial lineages, delineating associations of several subtypes with cancer risk factors, including age, parity, and BRCA2 germline mutation. Of particular interest is a subset of alveolar cells termed basal-luminal (BL) cells, which exhibit poor transcriptional lineage fidelity, accumulate with age, and carry a gene signature associated with basal-like breast cancer. We further utilize a medium-depletion approach to identify molecular factors regulating cell-subtype proportion in organoids. Together, these data are a rich resource to elucidate diverse mammary cell states.

Computational identification of preneoplastic cells displaying high stemness and risk of cancer progression

Evidence points towards the differentiation state of cells as a marker of cancer risk and progression. Measuring the differentiation state of single cells in a preneoplastic population could thus enable novel strategies for early detection and risk prediction. Recent maps of somatic mutagenesis in normal tissues from young healthy individuals have revealed cancer driver mutations, indicating that these do not correlate well with differentiation state and that other molecular events also contribute to cancer development. We hypothesized that the differentiation state of single cells can be measured by estimating the regulatory activity of the transcription factors (TFs) that control differentiation within that cell lineage. To this end, we present a novel computational method called CancerStemID that estimates a stemness index of cells from single-cell RNA-Seq data. CancerStemID is validated in two human esophageal squamous cell carcinoma (ESCC) cohorts, demonstrating how it can identify undifferentiated preneoplastic cells whose transcriptomic state is overrepresented in invasive cancer. Spatial transcriptomics and whole-genome bisulfite sequencing demonstrated that differentiation activity of tissue-specific TFs was decreased in cancer cells compared to the basal cell-of-origin layer and established that differentiation state correlated with differential DNA methylation at the promoters of these TFs, independently of underlying NOTCH1 and TP53 mutations. The findings were replicated in a mouse model of ESCC development, and the broad applicability of CancerStemID to other cancer-types was demonstrated. In summary, these data support an epigenetic stem-cell model of oncogenesis and highlight a novel computational strategy to identify stem-like preneoplastic cells that undergo positive selection.

A zebrafish reporter line reveals immune and neuronal expression of endogenous retrovirus

Endogenous retroviruses (ERVs) are fossils left in our genome from retrovirus infections of the past. Their sequences are part of every vertebrate genome and their random integrations are thought to have contributed to evolution. Although ERVs are mainly silenced by the host genome, they have been found to be activated in multiple disease states, such as auto-inflammatory disorders and neurological diseases. However, the numerous copies in mammalian genomes and the lack of tools to study them make defining their role in health and diseases challenging. In this study, we identified eight copies of the zebrafish endogenous retrovirus zferv. We created and characterised the first in vivo ERV reporter line in any species. Using a combination of live imaging, flow cytometry and single-cell RNA sequencing, we mapped zferv expression to early T cells and neurons. Thus, this new tool identified tissues expressing ERV in zebrafish, highlighting a potential role of ERV during brain development and strengthening the hypothesis that ERV play a role in immunity and neurological diseases. This transgenic line is therefore a suitable tool to study the function of ERV in health and diseases.

Cancer stem cell markers for liver cancer and pancreatic cancer

Cancer stem cells (CSC) theory has ushered in a new era of cancer research. Tumor recurrence, metastasis and chemotherapy resistance are all related to the existence of cancer stem cells. Further understanding of tumor heterogeneity will contribute to targeted treatment. Liver cancer and pancreatic cancer are common digestive gland tumors with high lethality. This article reviews the identification and isolation of CSC markers in hepatocellular carcinoma and pancreatic cancer. The markers related signal pathways are involved in the occurrence and development of tumors, and have a significant impact on the proliferation, metastasis and invasion of cancer cells, which can be used as potential molecular therapeutic targets. This study will be helpful to understand cancer stem cell like cells.

The Complicated Nature of Somatic mtDNA Mutations in Aging

Mitochondria are the main source of energy used to maintain cellular homeostasis. This aspect of mitochondrial biology underlies their putative role in age-associated tissue dysfunction. Proper functioning of the electron transport chain (ETC), which is partially encoded by the extra-nuclear mitochondrial genome (mtDNA), is key to maintaining this energy production. The acquisition of de novo somatic mutations that interrupt the function of the ETC have long been associated with aging and common diseases of the elderly. Yet, despite over 30 years of study, the exact role(s) mtDNA mutations play in driving aging and its associated pathologies remains under considerable debate. Furthermore, even fundamental aspects of age-related mtDNA mutagenesis, such as when mutations arise during aging, where and how often they occur across tissues, and the specific mechanisms that give rise to them, remain poorly understood. In this review, we address the current understanding of the somatic mtDNA mutations, with an emphasis of when, where, and how these mutations arise during aging. Additionally, we highlight current limitations in our knowledge and critically evaluate the controversies stemming from these limitations. Lastly, we highlight new and emerging technologies that offer potential ways forward in increasing our understanding of somatic mtDNA mutagenesis in the aging process.

RNA-Seq of Single Fish Cells - Seeking Out the Leukocytes Mediating Immunity in Teleost Fishes

The immune system is a complex and sophisticated biological system, spanning multiple levels of complexity, from the molecular level to that of tissue. Our current understanding of its function and complexity, of the heterogeneity of leukocytes, is a result of decades of concentrated efforts to delineate cellular markers using conventional methods of antibody screening and antigen identification. In mammalian models, this led to in-depth understanding of individual leukocyte subsets, their phenotypes, and their roles in health and disease. The field was further propelled forward by the development of single-cell (sc) RNA-seq technologies, offering an even broader and more integrated view of how cells work together to generate a particular response. Consequently, the adoption of scRNA-seq revealed the unexpected plasticity and heterogeneity of leukocyte populations and shifted several long-standing paradigms of immunology. This review article highlights the unprecedented opportunities offered by scRNA-seq technology to unveil the individual contributions of leukocyte subsets and their crosstalk in generating the overall immune responses in bony fishes. Single-cell transcriptomics allow identifying unseen relationships, and formulating novel hypotheses tailored for teleost species, without the need to rely on the limited number of fish-specific antibodies and pre-selected markers. Several recent studies on single-cell transcriptomes of fish have already identified previously unnoticed expression signatures and provided astonishing insights into the diversity of teleost leukocytes and the evolution of vertebrate immunity. Without a doubt, scRNA-seq in tandem with bioinformatics tools and state-of-the-art methods, will facilitate studying the teleost immune system by not only defining key markers, but also teaching us about lymphoid tissue organization, development/differentiation, cell-cell interactions, antigen receptor repertoires, states of health and disease, all across time and space in fishes. These advances will invite more researchers to develop the tools necessary to explore the immunology of fishes, which remain non-conventional animal models from which we have much to learn.

A robust and scalable graph neural network for accurate single-cell classification

Single-cell RNA sequencing (scRNA-seq) techniques provide high-resolution data on cellular heterogeneity in diverse tissues, and a critical step for the data analysis is cell type identification. Traditional methods usually cluster the cells and manually identify cell clusters through marker genes, which is time-consuming and subjective. With the launch of several large-scale single-cell projects, millions of sequenced cells have been annotated and it is promising to transfer labels from the annotated datasets to newly generated datasets. One powerful way for the transferring is to learn cell relations through the graph neural network (GNN), but traditional GNNs are difficult to process millions of cells due to the expensive costs of the message-passing procedure at each training epoch. Here, we have developed a robust and scalable GNN-based method for accurate single-cell classification (GraphCS), where the graph is constructed to connect similar cells within and between labelled and unlabeled scRNA-seq datasets for propagation of shared information. To overcome the slow information propagation of GNN at each training epoch, the diffused information is pre-calculated via the approximate Generalized PageRank algorithm, enabling sublinear complexity over cell numbers. Compared with existing methods, GraphCS demonstrates better performance on simulated, cross-platform, cross-species and cross-omics scRNA-seq datasets. More importantly, our model provides a high speed and scalability on large datasets, and can achieve superior performance for 1 million cells within 50 min.

Single-Cell RNA-Seq Technologies and Computational Analysis Tools: Application in Cancer Research

The recent maturation of single-cell RNA sequencing (scRNA-seq) provides unique opportunities for researchers to uncover new and potentially unexpected biological discoveries and to understand the complexity of tissues by transcriptomic profiling in individual cells. This review introduces the latest scRNA-seq techniques and platforms as well as their advantages and disadvantages. Moreover, we review computational tools and pipelines for analyzing scRNA-seq data, and their applications in cancer research, highlighting the important role of scRNA-seq techniques in this area.

Single-Cell RNA Sequencing of In Vitro Expanded Chondrocytes: MSC-Like Cells With No Evidence of Distinct Subsets

OBJECTIVE

To investigate the heterogeneity of in vitro expanded chondrocytes used for autologous chondrocyte implantation.

METHODS

Human articular chondrocytes were expanded in vitro for 14 days, sorted into 86 single cells using fluorescence-activated cell sorting and subjected to single-cell RNA sequencing. Principal component, Cross R² hierarchical clustering, and differential gene expression analyses were used for data evaluation. Flow cytometry and single-cell RT-qPCR (reverse transcriptase quantitative polymerase chain reaction) was used to validate the results of the RNA sequencing data Polyclonal chondrocyte populations from the same donor were differentiated in vitro toward the osteogenic and adipogenic lineages.

RESULTS

There was considerable variation in gene expression between individual cells, but we found no evidence for separate cell subpopulations based on principal component, hierarchical clustering, and differential gene expression analysis. Most of the cells expressed all the markers defining mesenchymal stem cells, and as polyclonal chondrocyte populations from the same donor were shown to differentiate into osteocytes and adipocytes in vitro, these cells formally qualify as mesenchymal stem cells.

CONCLUSIONS

In vitro expanded chondrocytes consist of one single population of cells with heterogeneity in gene expression between the cells. Dedifferentiated chondrocytes qualify as mesenchymal stem cells as they fulfill all the criteria suggested by the International Society for Cellular Therapy.

Functional coordination of non-myocytes plays a key role in adult zebrafish heart regeneration

Cardiac regeneration occurs primarily through proliferation of existing cardiomyocytes, but also involves complex interactions between distinct cardiac cell types including non-cardiomyocytes (non-CMs). However, the subpopulations, distinguishing molecular features, cellular functions, and intercellular interactions of non-CMs in heart regeneration remain largely unexplored. Using the LIGER algorithm, we assemble an atlas of cell states from 61,977 individual non-CM scRNA-seq profiles isolated at multiple time points during regeneration. This analysis reveals extensive non-CM cell diversity, including multiple macrophage (MC), fibroblast (FB), and endothelial cell (EC) subpopulations with unique spatiotemporal distributions, and suggests an important role for MC in inducing the activated FB and EC subpopulations. Indeed, pharmacological perturbation of MC function compromises the induction of the unique FB and EC subpopulations. Furthermore, we developed computational algorithm Topologizer to map the topological relationships and dynamic transitions between functional states. We uncover dynamic transitions between MC functional states and identify factors involved in mRNA processing and transcriptional regulation associated with the transition. Together, our single-cell transcriptomic analysis of non-CMs during cardiac regeneration provides a blueprint for interrogating the molecular and cellular basis of this process.

Unraveling the Heterogeneity and Ontogeny of Dendritic Cells Using Single-Cell RNA Sequencing

Dendritic cells (DCs) play essential roles in innate and adaptive immunity and show high heterogeneity and intricate ontogeny. Advances in high-throughput sequencing technologies, particularly single-cell RNA sequencing (scRNA-seq), have improved the understanding of DC subsets. In this review, we discuss in detail the remarkable perspectives in DC reclassification and ontogeny as revealed by scRNA-seq. Moreover, the heterogeneity and multifunction of DCs during diseases as determined by scRNA-seq are described. Finally, we provide insights into the challenges and future trends in scRNA-seq technologies and DC research.

Short chain fatty acids (SCFAs) improves TNBS-induced colitis in zebrafish

The short-chain fatty acids (SCFAs) are metabolites originated from the fermentation of dietary fibers and amino acids produced by the bacteria of the intestinal microbiota. The most abundant SCFAs, acetate, propionate, and butyrate, have been proposed as a treatment for inflammatory bowel diseases (IBDs) due to their anti-inflammatory properties. This work aimed to analyze the effects of the treatment of three combined SCFAs in TNBS-induced intestinal inflammation in zebrafish larvae. Here, we demonstrated that SCFAs significantly increased the survival of TNBS-exposed larvae, preserved the intestinal endocytic function, reduced the expression of inflammatory cytokines and the intestinal recruitment of neutrophils caused by TNBS. However, SCFAs treatment did not appear to avoid TNBS-induced tissue damage in the intestinal wall and did not restore the number of mucus-producing goblet cells. Finally, exposure to TNBS induced dysbiosis of the microbiota with an increase in Betaproteobacteria and Actinobacteria, while the treatment with SCFAs maintained these population levels similar to control. Thus, we demonstrate that the treatment of three combined SCFAs presented anti-inflammatory properties previously seen in mammals, opening an opportunity to use zebrafish to explore the potential benefit of these and other metabolites to treat inflammation.

Pioneer neutrophils release chromatin within in vivo swarms

Neutrophils are rapidly recruited to inflammatory sites where their coordinated migration forms clusters, a process termed neutrophil swarming. The factors that modulate early stages of neutrophil swarming are not fully understood, requiring the development of new in vivo models. Using transgenic zebrafish larvae to study endogenous neutrophil migration in a tissue damage model, we demonstrate that neutrophil swarming is a conserved process in zebrafish immunity, sharing essential features with mammalian systems. We show that neutrophil swarms initially develop around an individual pioneer neutrophil. We observed the violent release of extracellular cytoplasmic and nuclear fragments by the pioneer and early swarming neutrophils. By combining in vitro and in vivo approaches to study essential components of neutrophil extracellular traps (NETs), we provide in-depth characterisation and high-resolution imaging of the composition and morphology of these release events. Using a photoconversion approach to track neutrophils within developing swarms, we identify that the fate of swarm-initiating pioneer neutrophils involves extracellular chromatin release and that the key NET components gasdermin, neutrophil elastase, and myeloperoxidase are required for the swarming process. Together our findings demonstrate that release of cellular components by pioneer neutrophils is an initial step in neutrophil swarming at sites of tissue injury.

Essential role for Gata2 in modulating lineage output from hematopoietic stem cells in zebrafish

The differentiation of hematopoietic stem cells (HSCs) is tightly controlled to ensure a proper balance between myeloid and lymphoid cell output. GATA2 is a pivotal hematopoietic transcription factor required for generation and maintenance of HSCs. GATA2 is expressed throughout development, but because of early embryonic lethality in mice, its role during adult hematopoiesis is incompletely understood. Zebrafish contains 2 orthologs of GATA2: Gata2a and Gata2b, which are expressed in different cell types. We show that the mammalian functions of GATA2 are split between these orthologs. Gata2b-deficient zebrafish have a reduction in embryonic definitive hematopoietic stem and progenitor cell (HSPC) numbers, but are viable. This allows us to uniquely study the role of GATA2 in adult hematopoiesis. gata2b mutants have impaired myeloid lineage differentiation. Interestingly, this defect arises not in granulocyte-monocyte progenitors, but in HSPCs. Gata2b-deficient HSPCs showed impaired progression of the myeloid transcriptional program, concomitant with increased coexpression of lymphoid genes. This resulted in a decrease in myeloid-programmed progenitors and a relative increase in lymphoid-programmed progenitors. This shift in the lineage output could function as an escape mechanism to avoid a block in lineage differentiation. Our study helps to deconstruct the functions of GATA2 during hematopoiesis and shows that lineage differentiation flows toward a lymphoid lineage in the absence of Gata2b.