Cell Type Purification by Single-Cell Transcriptome-Trained Sorting

Regulation of blood-brain barrier integrity by Dmp1-expressing astrocytes through mitochondrial transfer

The blood-brain barrier (BBB) acts as the crucial physical filtration structure in the central nervous system. Here, we investigate the role of a specific subset of astrocytes in the regulation of BBB integrity. We showed that Dmp1-expressing astrocytes transfer mitochondria to endothelial cells via their endfeet for maintaining BBB integrity. Deletion of the Mitofusin 2 (Mfn2) gene in Dmp1-expressing astrocytes inhibited the mitochondrial transfer and caused BBB leakage. In addition, the decrease of MFN2 in astrocytes contributes to the age-associated reduction of mitochondrial transfer efficiency and thus compromises the integrity of BBB. Together, we describe a mechanism in which astrocytes regulate BBB integrity through mitochondrial transfer. Our findings provide innnovative insights into the cellular framework that underpins the progressive breakdown of BBB associated with aging and disease.

[WITHDRAWN] MIML: Multiplex Image Machine Learning for High Precision Cell Classification via Mechanical Traits within Microfluidic Systems

This paper has been withdrawn by Khayrul Islam.

Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets

Deconvolution of cell mixtures in "bulk" transcriptomic samples from homogenate human tissue is important for understanding disease pathologies. However, several experimental and computational challenges impede transcriptomics-based deconvolution approaches using single-cell/nucleus RNA-seq reference atlases. Cells from the brain and blood have substantially different sizes, total mRNA, and transcriptional activities, and existing approaches may quantify total mRNA instead of cell type proportions. Further, standards are lacking for the use of cell reference atlases and integrative analyses of single-cell and spatial transcriptomics data. We discuss how to approach these key challenges with orthogonal "gold standard" datasets for evaluating deconvolution methods.

Elucidating the neuroimmunology of traumatic brain injury: methodological approaches to unravel intercellular communication and function

The neuroimmunology of traumatic brain injury (TBI) has recently gained recognition as a crucial element in the secondary pathophysiological consequences that occur following neurotrauma. Both immune cells residing within the central nervous system (CNS) and those migrating from the periphery play significant roles in the development of secondary brain injury. However, the precise mechanisms governing communication between innate and adaptive immune cells remain incompletely understood, partly due to a limited utilization of relevant experimental models and techniques. Therefore, in this discussion, we outline current methodologies that can aid in the exploration of TBI neuroimmunology, with a particular emphasis on the interactions between resident neuroglial cells and recruited lymphocytes. These techniques encompass adoptive cell transfer, intra-CNS injection(s), selective cellular depletion, genetic manipulation, molecular neuroimaging, as well as in vitro co-culture systems and the utilization of organoid models. By incorporating key elements of both innate and adaptive immunity, these methods facilitate the examination of clinically relevant interactions. In addition to these preclinical approaches, we also detail an emerging avenue of research that seeks to leverage human biofluids. This approach enables the investigation of how resident and infiltrating immune cells modulate neuroglial responses after TBI. Considering the growing significance of neuroinflammation in TBI, the introduction and application of advanced methodologies will be pivotal in advancing translational research in this field.

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.

Cell Granularity Reflects Immune Cell Function and Enables Selection of Lymphocytes with Superior Attributes for Immunotherapy

In keeping with the rule of "form follows function", morphological aspects of a cell can reflect its role. Here, it is shown that the cellular granularity of a lymphocyte, represented by its intrinsic side scatter (SSC), is a potent indicator of its cell state and function. The granularity of a lymphocyte increases from naïve to terminal effector state. High-throughput cell-sorting yields a SSChigh population that can mediate immediate effector functions, and a highly prolific SSClow population that can give rise to the replenishment of the memory pool. CAR-T cells derived from the younger SSClow population possess desirable attributes for immunotherapy, manifested by increased naïve-like cells and stem cell memory (TSCM )-like cells together with a balanced CD4/CD8 ratio, as well as enhanced target-killing in vitro and in vivo. Altogether, lymphocyte segregation based on biophysical properties is an effective approach for label-free selection of cells that share collective functions and can have important applications for cell-based immunotherapies.

Microenvironmental control of hematopoietic stem cell fate via CXCL8 and protein kinase C

Altered hematopoietic stem cell (HSC) fate underlies primary blood disorders but microenvironmental factors controlling this are poorly understood. Genetically barcoded genome editing of synthetic target arrays for lineage tracing (GESTALT) zebrafish were used to screen for factors expressed by the sinusoidal vascular niche that alter the phylogenetic distribution of the HSC pool under native conditions. Dysregulated expression of protein kinase C delta (PKC-δ, encoded by prkcda) increases the number of HSC clones by up to 80% and expands polyclonal populations of immature neutrophil and erythroid precursors. PKC agonists such as cxcl8 augment HSC competition for residency within the niche and expand defined niche populations. CXCL8 induces association of PKC-δ with the focal adhesion complex, activating extracellular signal-regulated kinase (ERK) signaling and expression of niche factors in human endothelial cells. Our findings demonstrate the existence of reserve capacity within the niche that is controlled by CXCL8 and PKC and has significant impact on HSC phylogenetic and phenotypic fate.

Tissue specific imprinting on innate lymphoid cells during homeostasis and disease process revealed by integrative inference of single-cell transcriptomics

Introduction

Innate lymphoid cells (ILCs) are key components of the immune system, yet the similarity and distinction of the properties across tissues under homeostasis, inflammation and tumor process remain elusive.

Methods

Here we performed integrative inference of ILCs to reveal their transcriptional profiles and heterogeneity from single-cell genomics. We collected a large number of ILCs from human six different tissues which can represent unique immune niches (circulation, lymphoid tissue, normal and inflamed mucosa, tumor microenvironment), to systematically address the transcriptional imprinting.

Results

ILCs are profoundly imprinted by their organ of residence, and tissue-specific distinctions are apparent under pathological conditions. In the hepatocellular carcinoma microenvironment, we identified intermediate c-kit⁺ ILC2 population, and lin^-CD127^- NK-like cells that expressed markers of cytotoxicity including CCL5 and IFNG. Additionally, CD127⁺CD94⁺ ILC1s were preferentially enriched in inflamed ileum from patients with Crohn's disease.

Discussion

These analyses depicted a comprehensive characterization of ILC anatomical distribution and subset heterogeneity, and provided a base line for future temporal or spatial studies focused on tissue-specific ILC-mediated immunity.

Linking Expression of Cell-Surface Receptors with Transcription Factors by Computational Analysis of Paired Single-Cell Proteomes and Transcriptomes

Complex signaling and transcriptional programs control the development and physiology of specialized cell types. Genetic perturbations in these programs cause human cancers to arise from a diverse set of specialized cell types and developmental states. Understanding these complex systems and their potential to drive cancer is critical for the development of immunotherapies and druggable targets. Pioneering single-cell multi-omics technologies that analyze transcriptional states have been coupled with the expression of cell-surface receptors. This chapter describes SPaRTAN (Single-cell Proteomic and RNA-based Transcription factor Activity Network), a computational framework, to link transcription factors with cell-surface protein expression. SPaRTAN uses CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) data and cis-regulatory sites to model the effect of interactions between transcription factors and cell-surface receptors on gene expression. We demonstrate the pipeline for SPaRTAN using CITE-seq data from peripheral blood mononuclear cells.

Droplets microfluidics platform-A tool for single cell research

Cells are the most basic structural and functional units of living organisms. Studies of cell growth, differentiation, apoptosis, and cell-cell interactions can help scientists understand the mysteries of living systems. However, there is considerable heterogeneity among cells. Great differences between individuals can be found even within the same cell cluster. Cell heterogeneity can only be clearly expressed and distinguished at the level of single cells. The development of droplet microfluidics technology opens up a new chapter for single-cell analysis. Microfluidic chips can produce many nanoscale monodisperse droplets, which can be used as small isolated micro-laboratories for various high-throughput, precise single-cell analyses. Moreover, gel droplets with good biocompatibility can be used in single-cell cultures and coupled with biomolecules for various downstream analyses of cellular metabolites. The droplets are also maneuverable; through physical and chemical forces, droplets can be divided, fused, and sorted to realize single-cell screening and other related studies. This review describes the channel design, droplet generation, and control technology of droplet microfluidics and gives a detailed overview of the application of droplet microfluidics in single-cell culture, single-cell screening, single-cell detection, and other aspects. Moreover, we provide a recent review of the application of droplet microfluidics in tumor single-cell immunoassays, describe in detail the advantages of microfluidics in tumor research, and predict the development of droplet microfluidics at the single-cell level.

Single-Cell Sequencing in Rheumatic Diseases: New Insights from the Perspective of the Cell Type

Rheumatic diseases are a group of highly heterogeneous autoimmune and inflammatory disorders involving multiple systems. Dysfunction of immune and non-immune cells participates in the complex pathogenesis of rheumatic diseases. Therefore, studies on the abnormal activation of cell subtypes provided a specific basis for understanding the pathogenesis of rheumatic diseases, which promoted the accuracy of disease diagnosis and the effectiveness of various treatments. However, there was still a far way to achieve individualized precision medicine as the result of heterogeneity among cell subtypes. To obtain the biological information of cell subtypes, single-cell sequencing, a cutting-edge technology, is used for analyzing their genomes, transcriptomes, epigenetics, and proteomics. Novel results identified multiple cell subtypes in tissues of patients with rheumatic diseases by single-cell sequencing. Consequently, we provide an overview of recent applications of single-cell sequencing in rheumatic disease and cross-tissue to understand the cell subtypes and functions.

Stem cell-based multi-tissue platforms to model human autoimmune diabetes

BACKGROUND

Type 1 diabetes (T1D) is an autoimmune disease in which pancreatic insulin-producing β cells are specifically destroyed by the immune system. Understanding the initiation and progression of human T1D has been hampered by the lack of appropriate models that can reproduce the complexity and heterogeneity of the disease. The development of platforms combining multiple human pluripotent stem cell (hPSC) derived tissues to model distinct aspects of T1D has the potential to provide critical novel insights into the etiology and pathogenesis of the human disease.

SCOPE OF REVIEW

In this review, we summarize the state of hPSC differentiation approaches to generate cell types and tissues relevant to T1D, with a particular focus on pancreatic islet cells, T cells, and thymic epithelium. We present current applications as well as limitations of using these hPSC-derived cells for disease modeling and discuss efforts to optimize platforms combining multiple cell types to model human T1D. Finally, we outline remaining challenges and emphasize future improvements needed to accelerate progress in this emerging field of research.

MAJOR CONCLUSIONS

Recent advances in reprogramming approaches to create patient-specific induced pluripotent stem cell lines (iPSCs), genome engineering technologies to efficiently modify DNA of hPSCs, and protocols to direct their differentiation into mature cell types have empowered the use of stem cell derivatives to accurately model human disease. While challenges remain before complex interactions occurring in human T1D can be modeled with these derivatives, experiments combining hPSC-derived β cells and immune cells are already providing exciting insight into how these cells interact in the context of T1D, supporting the viability of this approach.

Aortic Cellular Diversity and Quantitative Genome-Wide Association Study Trait Prioritization Through Single-Nuclear RNA Sequencing of the Aneurysmal Human Aorta

BACKGROUND

Mural cells in ascending aortic aneurysms undergo phenotypic changes that promote extracellular matrix destruction and structural weakening. To explore this biology, we analyzed the transcriptional features of thoracic aortic tissue.

METHODS

Single-nuclear RNA sequencing was performed on 13 samples from human donors, 6 with thoracic aortic aneurysm, and 7 without aneurysm. Individual transcriptomes were then clustered based on transcriptional profiles. Clusters were used for between-disease differential gene expression analyses, subcluster analysis, and analyzed for intersection with genetic aortic trait data.

RESULTS

We sequenced 71 689 nuclei from human thoracic aortas and identified 14 clusters, aligning with 11 cell types, predominantly vascular smooth muscle cells (VSMCs) consistent with aortic histology. With unbiased methodology, we found 7 vascular smooth muscle cell and 6 fibroblast subclusters. Differentially expressed genes analysis revealed a vascular smooth muscle cell group accounting for the majority of differential gene expression. Fibroblast populations in aneurysm exhibit distinct behavior with almost complete disappearance of quiescent fibroblasts. Differentially expressed genes were used to prioritize genes at aortic diameter and distensibility genome-wide association study loci highlighting the genes JUN, LTBP4 (latent transforming growth factor beta-binding protein 1), and IL34 (interleukin 34) in fibroblasts, ENTPD1, PDLIM5 (PDZ and LIM domain 5), ACTN4 (alpha-actinin-4), and GLRX in vascular smooth muscle cells, as well as LRP1 in macrophage populations.

CONCLUSIONS

Using nuclear RNA sequencing, we describe the cellular diversity of healthy and aneurysmal human ascending aorta. Sporadic aortic aneurysm is characterized by differential gene expression within known cellular classes rather than by the appearance of novel cellular forms. Single-nuclear RNA sequencing of aortic tissue can be used to prioritize genes at aortic trait loci.

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.

Multi-Phenotypic Exosome Secretion Profiling Microfluidic Platform for Exploring Single-Cell Heterogeneity

Cellular phenotypic and functional heterogeneities have advanced cancer evolution and treatment resistance. Although exosome-bound proteins reflect cellular functions, single-cell exosomes are rarely profiled owing to the lack of effective platforms. Herein, the authors developed an integrated microfluidic platform consisting of a single-cell trapping chip and a spatially coded antibody barcode chip for the multiplexed outline of exosome secretion by single cells. Using this platform, five phenotypic exosomes of over 1 000 single cells are simultaneously profiled, in addition to inflammatory factor secretion from the same single cell. Also, a robust analysis workflow for single-cell secretion profiling is proposed to explore the intercellular heterogeneity, which integrated unsupervised clustering and linear clustering. When applied to the tumor cell lines of epithelial-origin and normal epithelial cell lines, the strategy identifies functionally heterogeneous subpopulations with unique secretion patterns. Notably, special functional cell subsets for unique phenotypic exosomes (HSP70⁺ , EPCAM⁺ ) are found within ovarian tumor cells. The strategy proposed offers a new analysis approach for cellular differential exosome secretion at single-cell resolution using inflammatory factors, ultimately reinforcing the understanding of cell-to-cell heterogeneity and tumor landscape, and providing a valuable universal platform for single-cell biomarker exploration in biological and clinical research.

Lessons from single-cell RNA sequencing of human islets

Islet dysfunction is central in type 2 diabetes and full-blown type 2 diabetes develops first when the beta cells lose their ability to secrete adequate amounts of insulin in response to raised plasma glucose. Several mechanisms behind beta cell dysfunction have been put forward but many important questions still remain. Furthermore, our understanding of the contribution of each islet cell type in type 2 diabetes pathophysiology has been limited by technical boundaries. Closing this knowledge gap will lead to a leap forward in our understanding of the islet as an organ and potentially lead to improved treatments. The development of single-cell RNA sequencing (scRNAseq) has led to a breakthrough for characterising the transcriptome of each islet cell type and several important observations on the regulation of cell-type-specific gene expression have been made. When it comes to identifying type 2 diabetes disease mechanisms, the outcome is still limited. Several studies have identified differentially expressed genes, although there is very limited consensus between the studies. As with all new techniques, scRNAseq has limitations; in addition to being extremely expensive, genes expressed at low levels may not be detected, noise may not be appropriately filtered and selection biases for certain cell types are at hand. Furthermore, recent advances suggest that commonly used computational tools may be suboptimal for analysis of scRNAseq data in small-scale studies. Fortunately, development of new computational tools holds promise for harnessing the full potential of scRNAseq data. Here we summarise how scRNAseq has contributed to increasing the understanding of various aspects of islet biology as well as type 2 diabetes disease mechanisms. We also focus on challenges that remain and propose steps to promote the utilisation of the full potential of scRNAseq in this area.

Characterization of Pipefish Immune Cell Populations Through Single-Cell Transcriptomics

Teleost adaptive immune systems have evolved with more flexibility than previously assumed. A particularly enigmatic system to address immune system modifications in the evolutionary past is represented by the Syngnathids, the family of pipefishes, seahorses and seadragons. These small fishes with their unique male pregnancy have lost the spleen as an important immune organ as well as a functional major histocompatibility class II (MHC II) pathway. How these evolutionary changes have impacted immune cell population dynamics have up to this point remained unexplored. Here, we present the first immune cell repertoire characterization of a syngnathid fish (Syngnathus typhle) using single-cell transcriptomics. Gene expression profiles of individual cells extracted from blood and head-kidney clustered in twelve putative cell populations with eight belonging to those with immune function. Upregulated cell marker genes identified in humans and teleosts were used to define cell clusters. While the suggested loss of CD4+ T-cells accompanied the loss of the MHC II pathway was supported, the upregulation of specific subtype markers within the T-cell cluster indicates subpopulations of regulatory T-cells (il2rb) and cytotoxic T-cells (gzma). Utilizing single-cell RNA sequencing this report is the first to characterize immune cell populations in syngnathids and provides a valuable foundation for future cellular classification and experimental work within the lineage.

Single-cell transcriptomics in human skin research: available technologies, technical considerations, and disease applications

Single‐cell technologies have revolutionized research in the last decade, including for skin biology. Single‐cell RNA sequencing has emerged as a powerful tool allowing the dissection of human disease pathophysiology at unprecedented resolution by assessing cell‐to‐cell variation, facilitating identification of rare cell populations and elucidating cellular heterogeneity. In dermatology, this technology has been widely applied to inflammatory skin disorders, fibrotic skin diseases, wound healing complications and cutaneous neoplasms. Here, we discuss the available technologies and technical considerations of single‐cell RNA sequencing and describe its applications to a broad spectrum of dermatological diseases.

Advancing root developmental research through single-cell technologies

Single-cell RNA-sequencing has greatly increased the spatiotemporal resolution of root transcriptomics data, but we are still only scratching the surface of its full potential. Despite the challenges that remain in the field, the orderly aligned structure of the Arabidopsis root meristem makes it specifically suitable for lineage tracing and trajectory analysis. These methods will become even more potent by increasing resolution and specificity using tissue-specific single-cell RNA-sequencing and spatial transcriptomics. Feeding multiple single-cell omics data sets into single-cell gene regulatory networks will accelerate the discovery of regulators of root development in multiple species. By providing transcriptome atlases for virtually any species, single-cell technologies could tempt many root developmental biologists to move beyond the comfort of the well-known Arabidopsis root meristem.

SPaRTAN, a computational framework for linking cell-surface receptors to transcriptional regulators

The identity and functions of specialized cell types are dependent on the complex interplay between signaling and transcriptional networks. Recently single-cell technologies have been developed that enable simultaneous quantitative analysis of cell-surface receptor expression with transcriptional states. To date, these datasets have not been used to systematically develop cell-context-specific maps of the interface between signaling and transcriptional regulators orchestrating cellular identity and function. We present SPaRTAN (Single-cell Proteomic and RNA based Transcription factor Activity Network), a computational method to link cell-surface receptors to transcription factors (TFs) by exploiting cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) datasets with cis-regulatory information. SPaRTAN is applied to immune cell types in the blood to predict the coupling of signaling receptors with cell context-specific TFs. Selected predictions are validated by prior knowledge and flow cytometry analyses. SPaRTAN is then used to predict the signaling coupled TF states of tumor infiltrating CD8+ T cells in malignant peritoneal and pleural mesotheliomas. SPaRTAN enhances the utility of CITE-seq datasets to uncover TF and cell-surface receptor relationships in diverse cellular states.

Troy/Tnfrsf19 marks epidermal cells that govern interfollicular epidermal renewal and cornification

The skin epidermis is a highly compartmentalized tissue consisting of a cornifying epithelium called the interfollicular epidermis (IFE) and associated hair follicles (HFs). Several stem cell populations have been described that mark specific compartments in the skin but none of them is specific to the IFE. Here, we identify Troy as a marker of IFE and HF infundibulum basal layer cells in developing and adult human and mouse epidermis. Genetic lineage-tracing experiments demonstrate that Troy-expressing basal cells contribute to long-term renewal of all layers of the cornifying epithelium. Single-cell transcriptomics and organoid assays of Troy-expressing cells, as well as their progeny, confirmed stem cell identity as well as the ability to generate differentiating daughter cells. In conclusion, we define Troy as a marker of epidermal basal cells that govern interfollicular epidermal renewal and cornification.

Image3C, a multimodal image-based and label-independent integrative method for single-cell analysis

Image-based cell classification has become a common tool to identify phenotypic changes in cell populations. However, this methodology is limited to organisms possessing well-characterized species-specific reagents (e.g., antibodies) that allow cell identification, clustering, and convolutional neural network (CNN) training. In the absence of such reagents, the power of image-based classification has remained mostly off-limits to many research organisms. We have developed an image-based classification methodology we named Image3C (Image-Cytometry Cell Classification) that does not require species-specific reagents nor pre-existing knowledge about the sample. Image3C combines image-based flow cytometry with an unbiased, high-throughput cell clustering pipeline and CNN integration. Image3C exploits intrinsic cellular features and non-species-specific dyes to perform de novo cell composition analysis and detect changes between different conditions. Therefore, Image3C expands the use of image-based analyses of cell population composition to research organisms in which detailed cellular phenotypes are unknown or for which species-specific reagents are not available.

A non-canonical type 2 immune response coordinates tuberculous granuloma formation and epithelialization

The central pathogen-immune interface in tuberculosis is the granuloma, a complex host immune structure that dictates infection trajectory and physiology. Granuloma macrophages undergo a dramatic transition in which entire epithelial modules are induced and define granuloma architecture. In tuberculosis, relatively little is known about the host signals that trigger this transition. Using the zebrafish-Mycobacterium marinum model, we identify the basis of granuloma macrophage transformation. Single-cell RNA-sequencing analysis of zebrafish granulomas and analysis of Mycobacterium tuberculosis-infected macaques reveal that, even in the presence of robust type 1 immune responses, countervailing type 2 signals associate with macrophage epithelialization. We find that type 2 immune signaling, mediated via stat6, is absolutely required for epithelialization and granuloma formation. In mixed chimeras, stat6 acts cell autonomously within macrophages, where it is required for epithelioid transformation and incorporation into necrotic granulomas. These findings establish the signaling pathway that produces the hallmark structure of mycobacterial infection.

New tools for 'ZEBRA-FISHING'

Zebrafish has been established as a classical model for developmental studies, yet in the past years, with the explosion of novel technological methods, the use of zebrafish as a model has expanded. One of the prominent fields that took advantage of zebrafish as a model organism early on is hematopoiesis, the process of blood cell generation from hematopoietic stem and progenitor cells (HSPCs). In zebrafish, HSPCs are born early during development in the aorta-gonad-mesonephros region and then translocate to the caudal hematopoietic tissue, where they expand and finally take residence in the kidney marrow. This journey is tightly regulated at multiple levels from extracellular signals to chromatin. In order to delineate the mechanistic underpinnings of this process, next-generation sequencing techniques could be an important ally. Here, we describe genome-wide approaches that have been undertaken to delineate zebrafish hematopoiesis.

Gut CD4+ T cell phenotypes are a continuum molded by microbes, not by TH archetypes

CD4+ effector lymphocytes (Teff) are traditionally classified by the cytokines they produce. To determine the states that Teff cells actually adopt in frontline tissues in vivo, we applied single-cell transcriptome and chromatin analyses to colonic Teff cells in germ-free or conventional mice or in mice after challenge with a range of phenotypically biasing microbes. Unexpected subsets were marked by the expression of the interferon (IFN) signature or myeloid-specific transcripts, but transcriptome or chromatin structure could not resolve discrete clusters fitting classic helper T cell (TH) subsets. At baseline or at different times of infection, transcripts encoding cytokines or proteins commonly used as TH markers were distributed in a polarized continuum, which was functionally validated. Clones derived from single progenitors gave rise to both IFN-γ- and interleukin (IL)-17-producing cells. Most of the transcriptional variance was tied to the infecting agent, independent of the cytokines produced, and chromatin variance primarily reflected activities of activator protein (AP)-1 and IFN-regulatory factor (IRF) transcription factor (TF) families, not the canonical subset master regulators T-bet, GATA3 or RORγ.

Tumor-infiltrating dendritic cell states are conserved across solid human cancers

Dendritic cells (DCs) contribute a small fraction of the tumor microenvironment but are emerging as an essential antitumor component based on their ability to foster T cell immunity and immunotherapy responses. Here, we discuss our expanding view of DC heterogeneity in human tumors, as revealed with meta-analysis of single-cell transcriptome profiling studies. We further examine tumor-infiltrating DC states that are conserved across patients, cancer types, and species and consider the fundamental and clinical relevance of these findings. Finally, we provide an outlook on research opportunities to further explore mechanisms governing tumor-infiltrating DC behavior and functions.

Single-cell proteo-genomic reference maps of the hematopoietic system enable the purification and massive profiling of precisely defined cell states

Single-cell genomics technology has transformed our understanding of complex cellular systems. However, excessive cost and a lack of strategies for the purification of newly identified cell types impede their functional characterization and large-scale profiling. Here, we have generated high-content single-cell proteo-genomic reference maps of human blood and bone marrow that quantitatively link the expression of up to 197 surface markers to cellular identities and biological processes across all main hematopoietic cell types in healthy aging and leukemia. These reference maps enable the automatic design of cost-effective high-throughput cytometry schemes that outperform state-of-the-art approaches, accurately reflect complex topologies of cellular systems and permit the purification of precisely defined cell states. The systematic integration of cytometry and proteo-genomic data enables the functional capacities of precisely mapped cell states to be measured at the single-cell level. Our study serves as an accessible resource and paves the way for a data-driven era in cytometry.

Phosphatidylinositol-3 kinase signaling controls survival and stemness of hematopoietic stem and progenitor cells

Hematopoietic stem and progenitor cells (HSPCs) are multipotent cells giving rise to all blood lineages during life. HSPCs emerge from the ventral wall of the dorsal aorta (VDA) during a specific timespan in embryonic development through endothelial hematopoietic transition (EHT). We investigated the ontogeny of HSPCs in mutant zebrafish embryos lacking functional pten, an important tumor suppressor with a central role in cell signaling. Through in vivo live imaging, we discovered that in pten mutant embryos a proportion of the HSPCs died upon emergence from the VDA, an effect rescued by inhibition of phosphatidylinositol-3 kinase (PI3K). Surprisingly, inhibition of PI3K in wild-type embryos also induced HSPC death. Surviving HSPCs colonized the caudal hematopoietic tissue (CHT) normally and committed to all blood lineages. Single-cell RNA sequencing indicated that inhibition of PI3K enhanced survival of multipotent progenitors, whereas the number of HSPCs with more stem-like properties was reduced. At the end of the definitive wave, loss of Pten caused a shift to more restricted progenitors at the expense of HSPCs. We conclude that PI3K signaling tightly controls HSPCs survival and both up- and downregulation of PI3K signaling reduces stemness of HSPCs.

Society for Immunotherapy of Cancer clinical and biomarkers data sharing resource document: Volume II-practical challenges

The development of strongly predictive validated biomarkers is essential for the field of immuno-oncology (IO) to advance. The highly complex, multifactorial data sets required to develop these biomarkers necessitate effective, responsible data-sharing efforts in order to maximize the scientific knowledge and utility gained from their collection. While the sharing of clinical- and safety-related trial data has already been streamlined to a large extent, the sharing of biomarker-aimed clinical trial derived data and data sets has been met with a number of hurdles that have impaired the progression of biomarkers from hypothesis to clinical use. These hurdles include technical challenges associated with the infrastructure, technology, workforce, and sustainability required for clinical biomarker data sharing. To provide guidance and assist in the navigation of these challenges, the Society for Immunotherapy of Cancer (SITC) Biomarkers Committee convened to outline the challenges that researchers currently face, both at the conceptual level (Volume I) and at the technical level (Volume II). The committee also suggests possible solutions to these problems in the form of professional standards and harmonized requirements for data sharing, assisting in continued progress toward effective, clinically relevant biomarkers in the IO setting.

Coupled scRNA-Seq and Intracellular Protein Activity Reveal an Immunosuppressive Role of TREM2 in Cancer

Cell function and activity are regulated through integration of signaling, epigenetic, transcriptional, and metabolic pathways. Here, we introduce INs-seq, an integrated technology for massively parallel recording of single-cell RNA sequencing (scRNA-seq) and intracellular protein activity. We demonstrate the broad utility of INs-seq for discovering new immune subsets by profiling different intracellular signatures of immune signaling, transcription factor combinations, and metabolic activity. Comprehensive mapping of Arginase 1-expressing cells within tumor models, a metabolic immune signature of suppressive activity, discovers novel Arg1⁺ Trem2⁺ regulatory myeloid (Mreg) cells and identifies markers, metabolic activity, and pathways associated with these cells. Genetic ablation of Trem2 in mice inhibits accumulation of intra-tumoral Mreg cells, leading to a marked decrease in dysfunctional CD8⁺ T cells and reduced tumor growth. This study establishes INs-seq as a broadly applicable technology for elucidating integrated transcriptional and intra-cellular maps and identifies the molecular signature of myeloid suppressive cells in tumors.

The Application of Single-Cell RNA Sequencing in Vaccinology

Single-cell RNA sequencing allows highly detailed profiling of cellular immune responses from limited-volume samples, advancing prospects of a new era of systems immunology. The power of single-cell RNA sequencing offers various opportunities to decipher the immune response to infectious diseases and vaccines. Here, we describe the potential uses of single-cell RNA sequencing methods in prophylactic vaccine development, concentrating on infectious diseases including COVID-19. Using examples from several diseases, we review how single-cell RNA sequencing has been used to evaluate the immunological response to different vaccine platforms and regimens. By highlighting published and unpublished single-cell RNA sequencing studies relevant to vaccinology, we discuss some general considerations how the field could be enriched with the widespread adoption of this technology.

Cell Reprogramming With CRISPR/Cas9 Based Transcriptional Regulation Systems

The speed of reprogramming technologies evolution is rising dramatically in modern science. Both the scientific community and health workers depend on such developments due to the lack of safe autogenic cells and tissues for regenerative medicine, genome editing tools and reliable screening techniques. To perform experiments efficiently and to propel the fundamental science it is important to keep up with novel modifications and techniques that are being discovered almost weekly. One of them is CRISPR/Cas9 based genome and transcriptome editing. The aim of this article is to summarize currently existing CRISPR/Cas9 applications for cell reprogramming, mainly, to compare them with other non-CRISPR approaches and to highlight future perspectives and opportunities.

Single-cell biomedicine: roles of single-cell nuclear elements

Single-cell biomedicine, a new merging discipline of cell biology and medicine to improve the life quality of patients, gains high priority in cell biology and toxicology. Single-cell nuclear elements are specially focused and headlined to understand regulatory mechanisms by which transcriptional factors, DNA elements, and genome organization interact with each other and contribute to the developmental evolution and dynamic formation of genotoxicity. Cell molecular phenomics, clonal genotypes, and structural metamorphoses during the cell cycle at single-cell level provide deep insights to understanding mechanism-based bridges between cell biology and toxicology, between cell sensitive and resistance, and between chronic diseases and cancer.