Single-cell mRNA quantification and differential analysis with Census

Longitudinal single-cell RNA-seq of hESCs-derived retinal organoids

Human retina development involves multiple well-studied signaling pathways that promote the genesis of a wide arrange of different cell types in a complex architectural structure. Human embryonic stem cells (hESCs)-derived retinal organoids could recapitulate the human retinal development. We performed single-cell RNA-seq of retinal organoids from 5 time points (D36, D66, D96, D126, D186) and identified 9 distinct populations of cells. In addition, we analyzed the molecular characteristics of each main population and followed them from genesis to maturity by pseudotime analysis and characterized the cell-cell interactions between different cell types. Interestingly, we identified insulin receptor (INSR) as a specifically expressed receptor involved in the genesis of photoreceptors, and pleiothropin (PTN)-protein tyrosine phosphatase receptor type Z1 (PTPRZ1) as a mediator of a previously unknown interaction between Müller and retinal progenitor cells. Taken together, these findings provide a rich transcriptome-based lineage map for studying human retinal development and modeling developmental disorders in retinal organoids.

Fixed single-cell RNA sequencing for understanding virus infection and host response

Single-cell transcriptomic studies that require intracellular protein staining, rare cell sorting, or inactivation of infectious pathogens are severely limited because current high-throughput RNA sequencing methods are incompatible with paraformaldehyde treatment, a common tissue and cell fixation and preservation technique. Here we present FD-seq, a high-throughput method for droplet-based RNA sequencing of paraformaldehyde-fixed, stained and sorted single-cells. We show that FD-seq preserves the mRNA integrity and relative abundances during fixation and subsequent cell retrieval. Furthermore, FD-seq detects a higher number of genes and transcripts than methanol fixation. We applied FD-seq to investigate two important questions in Virology. First, by analyzing a rare population of cells supporting lytic reactivation of the human tumor virus KSHV, we identified TMEM119 as a host factor that mediates viral reactivation. Second, we found that upon infection with the betacoronavirus OC43, which causes the common cold and is a close relative of SARS-CoV-2, pro-inflammatory pathways are primarily upregulated in lowly-infected cells that are exposed to the virus but fail to express high levels of viral genes. FD-seq thus enables integrating phenotypic with transcriptomic information in rare cell populations, and preserving and inactivating pathogenic samples that cannot be handled under regular biosafety measures.

Bcl9 Depletion Modulates Endothelial Cell in Tumor Immune Microenvironment in Colorectal Cancer Tumor

Tumor endothelial cells are an important part of the tumor microenvironment, and angiogenesis inhibitory therapy has shown potential in tumor treatment. However, which subtypes of tumor endothelial cells are distributed in tumors, what are the differences between tumor endothelial cells and normal endothelial cells, and what is the mechanism of angiogenesis inhibitory therapy at the histological level, are all need to be resolved urgently. Using single-cell mRNA sequencing, we analyzed 12 CT26 colon cancer samples from mice, and found that knockdown of the downstream factor BCL9 in the Wnt signaling pathway or inhibitor-mediated functional inhibition can modulate tumor endothelial cells at a relatively primitive stage, inhibiting their differentiation into further extracellular matrix construction and angiogenesis functions. Furthermore, we propose a BCL9-endo-Score based on the differential expression of cells related to different states of BCL9 functions. Using published data sets with normal endothelial cells, we found that this score can characterize endothelial cells at different stages of differentiation. Finally, in the The Cancer Genome Atlas (TCGA) pan-cancer database, we found that BCL9-endo-Score can well predict the prognosis of diseases including colon cancer, kidney cancer and breast cancer, and identified the markers of these tumor subtypes, provide a basis for the prognosis prediction of patients with such types of tumor. Our data also contributed knowledge for tumor precision treatment with angiogenesis inhibitory therapy by targeting the Wnt signaling pathway.

Inhibitory signaling sustains a distinct early memory CD8+ T cell precursor that is resistant to DNA damage

The developmental origins of memory T cells remain incompletely understood. During the expansion phase of acute viral infection, we identified a distinct subset of virus-specific CD8⁺ T cells that possessed distinct characteristics including expression of CD62L, T cell factor 1 (TCF-1), and Eomesodermin; relative quiescence; expression of activation markers; and features of limited effector differentiation. These cells were a quantitatively minor subpopulation of the TCF-1⁺ pool and exhibited self-renewal, heightened DNA damage surveillance activity, and preferential long-term recall capacity. Despite features of memory and somewhat restrained proliferation during the expansion phase, this subset displayed evidence of stronger TCR signaling than other responding CD8⁺ T cells, coupled with elevated expression of multiple inhibitory receptors including programmed cell death 1 (PD-1), lymphocyte activating gene 3 (LAG-3), cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), CD5, and CD160. Genetic ablation of PD-1 and LAG-3 compromised the formation of this CD62L^hi TCF-1⁺ subset and subsequent CD8⁺ T cell memory. Although central memory phenotype CD8⁺ T cells were formed in the absence of these cells, subsequent memory CD8⁺ T cell recall responses were compromised. Together, these results identify an important link between genome integrity maintenance and CD8⁺ T cell memory. Moreover, the data indicate a role for inhibitory receptors in preserving key memory CD8⁺ T cell precursors during initial activation and differentiation. Identification of this rare subpopulation within the memory CD8⁺ T cell precursor pool may help reconcile models of the developmental origin of long-term CD8⁺ T cell memory.

Single cell transcriptomic analysis of human pluripotent stem cell chondrogenesis

The therapeutic application of human induced pluripotent stem cells (hiPSCs) for cartilage regeneration is largely hindered by the low yield of chondrocytes accompanied by unpredictable and heterogeneous off-target differentiation of cells during chondrogenesis. Here, we combine bulk RNA sequencing, single cell RNA sequencing, and bioinformatic analyses, including weighted gene co-expression analysis (WGCNA), to investigate the gene regulatory networks regulating hiPSC differentiation under chondrogenic conditions. We identify specific WNTs and MITF as hub genes governing the generation of off-target differentiation into neural cells and melanocytes during hiPSC chondrogenesis. With heterocellular signaling models, we further show that WNT signaling produced by off-target cells is responsible for inducing chondrocyte hypertrophy. By targeting WNTs and MITF, we eliminate these cell lineages, significantly enhancing the yield and homogeneity of hiPSC-derived chondrocytes. Collectively, our findings identify the trajectories and molecular mechanisms governing cell fate decision in hiPSC chondrogenesis, as well as dynamic transcriptome profiles orchestrating chondrocyte proliferation and differentiation.

Induced organoids derived from patients with ulcerative colitis recapitulate colitic reactivity

The pathogenesis of ulcerative colitis (UC), a major type of inflammatory bowel disease, remains unknown. No model exists that adequately recapitulates the complexity of clinical UC. Here, we take advantage of induced pluripotent stem cells (iPSCs) to develop an induced human UC-derived organoid (iHUCO) model and compared it with the induced human normal organoid model (iHNO). Notably, iHUCOs recapitulated histological and functional features of primary colitic tissues, including the absence of acidic mucus secretion and aberrant adherens junctions in the epithelial barrier both in vitro and in vivo. We demonstrate that the CXCL8/CXCR1 axis was overexpressed in iHUCO but not in iHNO. As proof-of-principle, we show that inhibition of CXCL8 receptor by the small-molecule non-competitive inhibitor repertaxin attenuated the progression of UC phenotypes in vitro and in vivo. This patient-derived organoid model, containing both epithelial and stromal compartments, will generate new insights into the underlying pathogenesis of UC while offering opportunities to tailor interventions to the individual patient.

Differences in TCR repertoire and T cell activation underlie the divergent outcomes of antitumor immune responses in tumor-eradicating versus tumor-progressing hosts

Background

Antitumor immunity is highly heterogeneous between individuals; however, underlying mechanisms remain elusive, despite their potential to improve personalized cancer immunotherapy. Head and neck squamous cell carcinomas (HNSCCs) vary significantly in immune infiltration and therapeutic responses between patients, demanding a mouse model with appropriate heterogeneity to investigate mechanistic differences.

Methods

We developed a unique HNSCC mouse model to investigate underlying mechanisms of heterogeneous antitumor immunity. This model system may provide a better control for tumor-intrinsic and host-genetic variables, thereby uncovering the contribution of the adaptive immunity to tumor eradication. We employed single-cell T-cell receptor (TCR) sequencing coupled with single-cell RNA sequencing to identify the difference in TCR repertoire of CD8 tumor-infiltrating lymphocytes (TILs) and the unique activation states linked with different TCR clonotypes.

Results

We discovered that genetically identical wild-type recipient mice responded heterogeneously to the same squamous cell carcinoma tumors orthotopically transplanted into the buccal mucosa. While tumors initially grew in 100% of recipients and most developed aggressive tumors, ~25% of recipients reproducibly eradicated tumors without intervention. Heterogeneous antitumor responses were dependent on CD8 T cells. Consistently, CD8 TILs in regressing tumors were significantly increased and more activated. Single-cell TCR-sequencing revealed that CD8 TILs from both growing and regressing tumors displayed evidence of clonal expansion compared with splenic controls. However, top TCR clonotypes and TCR specificity groups appear to be mutually exclusive between regressing and growing TILs. Furthermore, many TCRα/TCRβ sequences only occur in one recipient. By coupling single-cell transcriptomic analysis with unique TCR clonotypes, we found that top TCR clonotypes clustered in distinct activation states in regressing versus growing TILs. Intriguingly, the few TCR clonotypes shared between regressors and progressors differed greatly in their activation states, suggesting a more dominant influence from tumor microenvironment than TCR itself on T cell activation status.

Conclusions

We reveal that intrinsic differences in the TCR repertoire of TILs and their different transcriptional trajectories may underlie the heterogeneous antitumor immune responses in different hosts. We suggest that antitumor immune responses are highly individualized and different hosts employ different TCR specificities against the same tumors, which may have important implications for developing personalized cancer immunotherapy.

Transcriptional profiling of pediatric cholestatic livers identifies three distinct macrophage populations

Background & aims

Limited understanding of the role for specific macrophage subsets in the pathogenesis of cholestatic liver injury is a barrier to advancing medical therapy. Macrophages have previously been implicated in both the mal-adaptive and protective responses in obstructive cholestasis. Recently two macrophage subsets were identified in non-diseased human liver; however, no studies to date fully define the heterogeneous macrophage subsets during the pathogenesis of cholestasis. Here, we aim to further characterize the transcriptional profile of macrophages in pediatric cholestatic liver disease.

Methods

We isolated live hepatic immune cells from patients with biliary atresia (BA), Alagille syndrome (ALGS), and non-cholestatic pediatric liver by fluorescence activated cell sorting. Through single-cell RNA sequencing analysis and immunofluorescence, we characterized cholestatic macrophages. We next compared the transcriptional profile of pediatric cholestatic and non-cholestatic macrophage populations to previously published data on normal adult hepatic macrophages.

Results

We identified 3 distinct macrophage populations across cholestatic liver samples and annotated them as lipid-associated macrophages, monocyte-like macrophages, and adaptive macrophages based on their transcriptional profile. Immunofluorescence of liver tissue using markers for each subset confirmed their presence across BA (n = 6) and ALGS (n = 6) patients. Cholestatic macrophages demonstrated reduced expression of immune regulatory genes as compared to normal hepatic macrophages and were distinct from macrophage populations defined in either healthy adult or pediatric non-cholestatic liver.

Conclusions

We are the first to perform single-cell RNA sequencing on human pediatric cholestatic liver and identified three macrophage subsets with distinct transcriptional signatures from healthy liver macrophages. Further analyses will identify similarities and differences in these macrophage sub-populations across etiologies of cholestatic liver disease. Taken together, these findings may allow for future development of targeted therapeutic strategies to reprogram macrophages to an immune regulatory phenotype and reduce cholestatic liver injury.

Single-Cell RNA Sequencing of Tocilizumab-Treated Peripheral Blood Mononuclear Cells as an in vitro Model of Inflammation

COVID-19 has posed a significant threat to global health. Early data has revealed that IL-6, a key regulatory cytokine, plays an important role in the cytokine storm of COVID-19. Multiple trials are therefore looking at the effects of Tocilizumab, an IL-6 receptor antibody that inhibits IL-6 activity, on treatment of COVID-19, with promising findings. As part of a clinical trial looking at the effects of Tocilizumab treatment on kidney transplant recipients with subclinical rejection, we performed single-cell RNA sequencing of comparing stimulated PBMCs before and after Tocilizumab treatment. We leveraged this data to create an in vitro cytokine storm model, to better understand the effects of Tocilizumab in the presence of inflammation. Tocilizumab-treated cells had reduced expression of inflammatory-mediated genes and biologic pathways, particularly amongst monocytes. These results support the hypothesis that Tocilizumab may hinder the cytokine storm of COVID-19, through a demonstration of biologic impact at the single-cell level.

Expression pattern determines regulatory logic

Large amounts of effort have been invested in trying to understand how a single genome is able to specify the identity of hundreds of cell types. Inspired by some aspects of Caenorhabditis elegans biology, we implemented an in silico evolutionary strategy to produce gene regulatory networks (GRNs) that drive cell-specific gene expression patterns, mimicking the process of terminal cell differentiation. Dynamics of the gene regulatory networks are governed by a thermodynamic model of gene expression, which uses DNA sequences and transcription factor degenerate position weight matrixes as input. In a version of the model, we included chromatin accessibility. Experimentally, it has been determined that cell-specific and broadly expressed genes are regulated differently. In our in silico evolved GRNs, broadly expressed genes are regulated very redundantly and the architecture of their cis-regulatory modules is different, in accordance to what has been found in C. elegans and also in other systems. Finally, we found differences in topological positions in GRNs between these two classes of genes, which help to explain why broadly expressed genes are so resilient to mutations. Overall, our results offer an explanatory hypothesis on why broadly expressed genes are regulated so redundantly compared to cell-specific genes, which can be extrapolated to phenomena such as ChIP-seq HOT regions.

Normalization of Single-Cell RNA-Seq Data

Normalization is an important step in the analysis of single-cell RNA-seq data. While no single method outperforms all others in all datasets, the choice of normalization can have profound impact on the results. Data-driven metrics can be used to rank normalization methods and select the best performers. Here, we show how to use R/Bioconductor to calculate normalization factors, apply them to compute normalized data, and compare several normalization approaches. Finally, we briefly show how to perform downstream analysis steps on the normalized data.

Transcriptional Profiling During Neural Conversion

The processes that underlie neuronal conversion ultimately involve a reorganization of transcriptional networks to establish a neuronal cell fate. As such, transcriptional profiling is a key component toward understanding this process. In this chapter, we will discuss methods of elucidating transcriptional networks during neuronal reprogramming and considerations that should be incorporated in experimental design.

Single-cell transcriptomics identifies limbal stem cell population and cell types mapping its differentiation trajectory in limbal basal epithelium of human cornea

PURPOSE

This study aimed to uncover novel cell types in heterogenous basal limbus of human cornea for identifying LSC at single cell resolution.

METHODS

Single cells of human limbal basal epithelium were isolated from young donor corneas. Single-cell RNA-Sequencing was performed using 10x Genomics platform, followed by clustering cell types through the graph-based visualization method UMAP and unbiased computational informatic analysis. Tissue RNA in situ hybridization with RNAscope, immunofluorescent staining and multiple functional assays were performed using human corneas and limbal epithelial culture models.

RESULTS

Single-cell transcriptomics of 16,360 limbal basal cells revealed 12 cell clusters belonging to three lineages. A smallest cluster (0.4% of total cells) was identified as LSCs based on their quiescent and undifferentiated states with enriched marker genes for putative epithelial stem cells. TSPAN7 and SOX17 are discovered and validated as new LSC markers based on their exclusive expression pattern and spatial localization in limbal basal epithelium by RNAscope and immunostaining, and functional role in cell growth and tissue regeneration models with RNA interference in cultures. Interestingly, five cell types/states mapping a developmental trajectory of LSC from quiescence to proliferation and differentiation are uncovered by Monocle3 and CytoTRACE pseudotime analysis. The transcription factor networks linking novel signaling pathways are revealed to maintain LSC stemness.

CONCLUSIONS

This human corneal scRNA-Seq identifies the LSC population and uncovers novel cell types mapping the differentiation trajectory in heterogenous limbal basal epithelium. The findings provide insight into LSC concept and lay the foundation for understanding the corneal homeostasis and diseases.

A primer on single-cell genomics in myeloid biology

PURPOSE OF REVIEW

Understanding the fast-moving field of single-cell technologies, as applied to myeloid biology, requires an appreciation of basic molecular, informatics, and biological concepts. Here, we highlight both key and recent articles to illustrate basic concepts for those new to molecular single-cell analyses in myeloid hematology.

RECENT FINDINGS

Recent studies apply single-cell omics to discover novel cell populations, construct relationships between cell populations, reconfigure the organization of hematopoiesis, and study hematopoietic lineage tree and fate choices. Accompanying development of technologies, new informatic tools have emerged, providing exciting new insights.

SUMMARY

Hematopoietic stem and progenitor cells are regulated by complex intrinsic and extrinsic factors to produce blood cell types. In this review, we discuss recent advances in single-cell omics to profile these cells, methods to infer cell type identify, and trajectories from molecular omics data to ultimately derive new insights into hematopoietic stem and progenitor cell biology. We further discuss future applications of these technologies to understand hematopoietic cell interactions, function, and development. The goal is to offer a comprehensive overview of current single-cell technologies and their impact on our understanding of myeloid cell development for those new to single-cell analyses.

Dissecting the initiation of female meiosis in the mouse at single-cell resolution

Meiosis is one of the most finely orchestrated events during gametogenesis with distinct developmental patterns in males and females. However, the molecular mechanisms involved in this process remain not well known. Here, we report detailed transcriptome analyses of cell populations present in the mouse female gonadal ridges (E11.5) and the embryonic ovaries from E12.5 to E14.5 using single-cell RNA sequencing (scRNA seq). These periods correspond with the initiation and progression of meiosis throughout the first stage of prophase I. We identified 13 transcriptionally distinct cell populations and 7 transcriptionally distinct germ cell subclusters that correspond to mitotic (3 clusters) and meiotic (4 clusters) germ cells. By analysing cluster-specific gene expression profiles, we found four cell clusters correspond to different cell stages en route to meiosis and characterized their detailed transcriptome dynamics. Our scRNA seq analysis here represents a new important resource for deciphering the molecular pathways driving female meiosis initiation.

Toward uncharted territory of cellular heterogeneity: advances and applications of single-cell RNA-seq

Among single-cell analysis technologies, single-cell RNA-seq (scRNA-seq) has been one of the front runners in technical inventions. Since its induction, scRNA-seq has been well received and undergone many fast-paced technical improvements in cDNA synthesis and amplification, processing and alignment of next generation sequencing reads, differentially expressed gene calling, cell clustering, subpopulation identification, and developmental trajectory prediction. scRNA-seq has been exponentially applied to study global transcriptional profiles in all cell types in humans and animal models, healthy or with diseases, including cancer. Accumulative novel subtypes and rare subpopulations have been discovered as potential underlying mechanisms of stochasticity, differentiation, proliferation, tumorigenesis, and aging. scRNA-seq has gradually revealed the uncharted territory of cellular heterogeneity in transcriptomes and developed novel therapeutic approaches for biomedical applications. This review of the advancement of scRNA-seq methods provides an exploratory guide of the quickly evolving technical landscape and insights of focused features and strengths in each prominent area of progress.

Cross-Comparison of Human iPSC Motor Neuron Models of Familial and Sporadic ALS Reveals Early and Convergent Transcriptomic Disease Signatures

Induced pluripotent stem cell (iPSC)-derived neural cultures from amyotrophic lateral sclerosis (ALS) patients can model disease phenotypes. However, heterogeneity arising from genetic and experimental variability limits their utility, impacting reproducibility and the ability to track cellular origins of pathogenesis. Here, we present methodologies using single-cell RNA sequencing (scRNA-seq) analysis to address these limitations. By repeatedly differentiating and applying scRNA-seq to motor neurons (MNs) from healthy, familial ALS, sporadic ALS, and genome-edited iPSC lines across multiple patients, batches, and platforms, we account for genetic and experimental variability toward identifying unified and reproducible ALS signatures. Combining HOX and developmental gene expression with global clustering, we anatomically classified cells into rostrocaudal, progenitor, and postmitotic identities. By relaxing statistical thresholds, we discovered genes in iPSC-MNs that were concordantly dysregulated in postmortem MNs and yielded predictive ALS markers in other human and mouse models. Our approach thus revealed early, convergent, and MN-resolved signatures of ALS.

Preparing Highly Viable Single-Cell Suspensions from Mouse Pancreatic Islets for Single-Cell RNA Sequencing

Pancreatic islets consist of several cell types, including alpha, beta, delta, epsilon, and PP cells. Due to cellular heterogeneity, it is challenging to interpret whole-islet transcriptome data. Single-cell transcriptomics offers a powerful method for investigating gene expression at the single-cell level and identifying cellular heterogeneity and subpopulations. Here, we describe a protocol for mouse pancreatic islet isolation, culturing, and dissociation into a single-cell suspension. This protocol yields highly viable cells for successful library preparation and single-cell RNA sequencing.

For complete details on the use and execution of this protocol, please refer to Lee et al. (2020).

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A detailed protocol for the isolation and culture of pancreatic islets from mice

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A procedure for dissociation of mouse islets into a single-cell suspension

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Method consistently yields optimal cell viability (90%) for scRNA sequencing

An Integrated Epigenomic and Transcriptomic Map of Mouse and Human αβ T Cell Development

αβ lineage T cells, most of which are CD4+ or CD8+ and recognize MHC I- or MHC II-presented antigens, are essential for immune responses and develop from CD4+CD8+ thymocytes. The absence of in vitro models and the heterogeneity of αβ thymocytes have hampered analyses of their intrathymic differentiation. Here, combining single-cell RNA and ATAC (chromatin accessibility) sequencing, we identified mouse and human αβ thymocyte developmental trajectories. We demonstrated asymmetric emergence of CD4+ and CD8+ lineages, matched differentiation programs of agonist-signaled cells to their MHC specificity, and identified correspondences between mouse and human transcriptomic and epigenomic patterns. Through computational analysis of single-cell data and binding sites for the CD4+-lineage transcription factor Thpok, we inferred transcriptional networks associated with CD4+- or CD8+-lineage differentiation, and with expression of Thpok or of the CD8+-lineage factor Runx3. Our findings provide insight into the mechanisms of CD4+ and CD8+ T cell differentiation and a foundation for mechanistic investigations of αβ T cell development.

Goals and approaches for each processing step for single-cell RNA sequencing data

Single-cell RNA sequencing (scRNA-seq) has enabled researchers to study gene expression at the cellular level. However, due to the extremely low levels of transcripts in a single cell and technical losses during reverse transcription, gene expression at a single-cell resolution is usually noisy and highly dimensional; thus, statistical analyses of single-cell data are a challenge. Although many scRNA-seq data analysis tools are currently available, a gold standard pipeline is not available for all datasets. Therefore, a general understanding of bioinformatics and associated computational issues would facilitate the selection of appropriate tools for a given set of data. In this review, we provide an overview of the goals and most popular computational analysis tools for the quality control, normalization, imputation, feature selection and dimension reduction of scRNA-seq data.

Human Pluripotent Stem Cell-Derived Kidney Organoids with Improved Collecting Duct Maturation and Injury Modeling

Maximizing the potential of human kidney organoids for drug testing and regenerative medicine and to model development and disease requires addressing cell immaturity, the lack of a mature collecting system, and off-target cell types. By independently generating two kidney progenitor cell populations-metanephric mesenchyme and ureteric bud (UB)-like cells-we could generate kidney organoids with a collecting system. We also identify the hormones aldosterone and arginine vasopressin (AVP) as critical to promote differentiation of collecting duct cell types including both principal cells (PCs) and intercalated cells (ICs). The resulting PCs express aquaporin-2 (AQP2) protein, which undergoes translocation to the apical membrane after vasopressin or forskolin stimulation. By single-cell RNA sequencing (scRNA-seq), we demonstrate improved proximal tubule maturation and reduced off-target cell populations. We also show appropriate downregulation of progenitor cell types, improved modeling of tubular injury, the presence of urothelium (Uro), and the ability of Notch pathway modulation to regulate PC:IC ratios during organoid development.

Contribution of PDGFRα lineage cells in adult mouse hematopoiesis

Platelet-derived growth factor receptor alpha (PDGFRα) is a dominant marker of mesodermal mesenchymal cells in mice. Previous studies demonstrated that PDGFRα-positive (PDGFRα+) mesodermal cells develop not only into mesenchymal cells but also into a subset of total hematopoietic cells (HCs) in the limited period during mouse embryogenesis. However, the precise characteristics of the PDGFRα lineage positive (PDGFRα Lin+) HCs in adult mouse hematopoiesis are largely unknown. In this study, we systematically evaluated the characteristics of PDGFRα Lin+ HCs in the bone marrow and peripheral blood using PDGFRα-CRE; ROSA^tdTomato mice. Flow cytometry analysis revealed that PDGFRα Lin+ HCs accounted for approximately 20% of total HCs in both the bone marrow and peripheral blood in adult mice. Compositions of myeloid and lymphoid subpopulations among CD45+ mononuclear cells were almost identical in both PDGFRα Lin+ and PDGFRα Lin- cells. Single-cell RNA-sequencing analysis also demonstrated that the transcriptomic signatures of the PDGFRα Lin+ HCs in the peripheral blood largely overlapped with those of the PDGFRα Lin- HCs, suggesting equivalent functions of the PDGFRα Lin+ and PDGFRα Lin- HCs. Although pathophysiological activities of the PDGFRα Lin + HCs were not evaluated, our data clearly demonstrate a significant role of the PDGFRα Lin + HCs in physiological hematopoiesis in adult mice.

Unraveling Targetable Systemic and Cell-Type-Specific Molecular Phenotypes of Alzheimer's and Parkinson's Brains With Digital Cytometry

Alzheimer's disease (AD) and Parkinson's disease (PD) are the two most common neurodegenerative disorders worldwide, with age being their major risk factor. The increasing worldwide life expectancy, together with the scarcity of available treatment choices, makes it thus pressing to find the molecular basis of AD and PD so that the causing mechanisms can be targeted. To study these mechanisms, gene expression profiles have been compared between diseased and control brain tissues. However, this approach is limited by mRNA expression profiles derived for brain tissues highly reflecting their degeneration in cellular composition but not necessarily disease-related molecular states. We therefore propose to account for cell type composition when comparing transcriptomes of healthy and diseased brain samples, so that the loss of neurons can be decoupled from pathology-associated molecular effects. This approach allowed us to identify genes and pathways putatively altered systemically and in a cell-type-dependent manner in AD and PD brains. Moreover, using chemical perturbagen data, we computationally identified candidate small molecules for specifically targeting the profiled AD/PD-associated molecular alterations. Our approach therefore not only brings new insights into the disease-specific and common molecular etiologies of AD and PD but also, in these realms, foster the discovery of more specific targets for functional and therapeutic exploration.

Heterogeneous bone-marrow stromal progenitors drive myelofibrosis via a druggable alarmin axis

Functional contributions of individual cellular components of the bone-marrow microenvironment to myelofibrosis (MF) in patients with myeloproliferative neoplasms (MPNs) are incompletely understood. We aimed to generate a comprehensive map of the stroma in MPNs/MFs on a single-cell level in murine models and patient samples. Our analysis revealed two distinct mesenchymal stromal cell (MSC) subsets as pro-fibrotic cells. MSCs were functionally reprogrammed in a stage-dependent manner with loss of their progenitor status and initiation of differentiation in the pre-fibrotic and acquisition of a pro-fibrotic and inflammatory phenotype in the fibrotic stage. The expression of the alarmin complex S100A8/S100A9 in MSC marked disease progression toward the fibrotic phase in murine models and in patient stroma and plasma. Tasquinimod, a small-molecule inhibiting S100A8/S100A9 signaling, significantly ameliorated the MPN phenotype and fibrosis in JAK2V617F-mutated murine models, highlighting that S100A8/S100A9 is an attractive therapeutic target in MPNs.

Exploring the role of RALYL in Alzheimer's disease reserve by network-based approaches

BACKGROUND

Alzheimer's disease (AD) reserve theory is based on specific individual characteristics that are associated with a higher resilience against neurodegeneration and its symptoms. A given degree of AD pathology may contribute to varying cognitive decline levels in different individuals. Although this phenomenon is attributed to reserve, the biological mechanisms that underpin it remain elusive, which restricts translational medicine research and treatment strategy development.

METHODS

Network-based approaches were integrated to identify AD reserve related genes. Then, AD brain transcriptomics data were clustered into co-expression modules, and a Bayesian network was developed using these modules plus AD reserve related phenotypes. The directed acyclic graph suggested that the module was strongly associated with AD reserve. The hub gene of the module of interest was filtered using the topological method. Validation was performed in the multi-AD brain transcriptomic dataset.

RESULTS

We revealed that the RALYL (RALY RNA Binding Protein-like) is the hub gene of the module which was highly associated with AD reserve related phenotypes. Pseudo-time projections of RALYL revealed the changes in relative expression drivers in the AD and control subjects over pseudo-time had distinct transcriptional states. Notably, the expression of RALYL decreased with the gradual progression of AD, and this corresponded to MMSE decline. Subjects with AD reserve exhibited significantly higher RALYL expression than those without AD reserve.

CONCLUSION

The present study suggests that RALYL may be associated with AD reserve, and it provides novel insights into the mechanisms of AD reserve and highlights the potential role of RALYL in this process.

Single-cell transcriptome profiling of an adult human cell atlas of 15 major organs

BACKGROUND

As core units of organ tissues, cells of various types play their harmonious rhythms to maintain the homeostasis of the human body. It is essential to identify the characteristics of cells in human organs and their regulatory networks for understanding the biological mechanisms related to health and disease. However, a systematic and comprehensive single-cell transcriptional profile across multiple organs of a normal human adult is missing.

RESULTS

We perform single-cell transcriptomes of 84,363 cells derived from 15 tissue organs of one adult donor and generate an adult human cell atlas. The adult human cell atlas depicts 252 subtypes of cells, including major cell types such as T, B, myeloid, epithelial, and stromal cells, as well as novel COCH+ fibroblasts and FibSmo cells, each of which is distinguished by multiple marker genes and transcriptional profiles. These collectively contribute to the heterogeneity of major human organs. Moreover, T cell and B cell receptor repertoire comparisons and trajectory analyses reveal direct clonal sharing of T and B cells with various developmental states among different tissues. Furthermore, novel cell markers, transcription factors, and ligand-receptor pairs are identified with potential functional regulations in maintaining the homeostasis of human cells among tissues.

CONCLUSIONS

The adult human cell atlas reveals the inter- and intra-organ heterogeneity of cell characteristics and provides a useful resource in uncovering key events during the development of human diseases in the context of the heterogeneity of cells and organs.

An atlas of immune cell exhaustion in HIV-infected individuals revealed by single-cell transcriptomics

Chronic infection with human immunodeficiency virus (HIV) can cause progressive loss of immune cell function, or exhaustion, which impairs control of virus replication. However, little is known about the development and maintenance, as well as heterogeneity of immune cell exhaustion. Here, we investigated the effects of HIV infection on immune cell exhaustion at the transcriptomic level by analyzing single-cell RNA sequencing of peripheral blood mononuclear cells from four healthy subjects (37,847 cells) and six HIV-infected donors (28,610 cells). We identified nine immune cell clusters and eight T cell subclusters, and three of these (exhausted CD4+ and CD8+ T cells and interferon-responsive CD8+ T cells) were detected only in samples from HIV-infected donors. An inhibitory receptor KLRG1 was identified in a HIV-1 specific exhausted CD8+ T cell population expressing KLRG1, TIGIT, and T-betdimEomeshi markers. Ex-vivo antibody blockade of KLRG1 restored the function of HIV-specific exhausted CD8+ T cells demonstrating the contribution of KLRG1+ population to T cell exhaustion and providing an immunotherapy target to treat HIV chronic infection. These data provide a comprehensive analysis of gene signatures associated with immune cell exhaustion during HIV infection, which could be useful in understanding exhaustion mechanisms and developing new cure therapies.

A novel cardiomyogenic role for Isl1+ neural crest cells in the inflow tract

The degree to which populations of cardiac progenitors (CPCs) persist in the postnatal heart remains a controversial issue in cardiobiology. To address this question, we conducted a spatiotemporally resolved analysis of CPC deployment dynamics, tracking cells expressing the pan-CPC gene Isl1 Most CPCs undergo programmed silencing during early cardiogenesis through proteasome-mediated and PRC2 (Polycomb group repressive complex 2)-mediated Isl1 repression, selectively in the outflow tract. A notable exception is a domain of cardiac neural crest cells (CNCs) in the inflow tract. These "dorsal CNCs" are regulated through a Wnt/β-catenin/Isl1 feedback loop and generate a limited number of trabecular cardiomyocytes that undergo multiple clonal divisions during compaction, to eventually produce ~10% of the biventricular myocardium. After birth, CNCs continue to generate cardiomyocytes that, however, exhibit diminished clonal amplification dynamics. Thus, although the postnatal heart sustains cardiomyocyte-producing CNCs, their regenerative potential is likely diminished by the loss of trabeculation-like proliferative properties.

What has single-cell RNA sequencing revealed about microglial neuroimmunology?

The use of single-cell RNA sequencing (scRNA-seq) in microglial research is increasing rapidly. The basic workflow of this approach consists of isolating single cells, followed by sequencing. scRNA-seq is capable of examining microglial heterogeneity on a cellular level. However, the results gained from applying this technique suffer from discrepancies due to differences between applied methods characteristics such as the number of cells sequenced and the depth of sequencing. This review aims to shed more light on the recent developments that happened in this field and how they are related to the methods used. To do that, we track the progress and limitations of various scRNA-seq methods currently available. The review then summarizes the current knowledge gained using scRNA-seq in the field of microglia, including novel subpopulations associated with function and development under homeostasis as well during several pathological conditions such as Alzheimer, lipopolysaccharide response, and HIV in relation to the methods employed. Our review points out that despite major developments found using this technique, current scRNA-seq methods suffer from high cost, low yields, and nonstandardization of generated data. Additional development of scRNA-seq methods will raise our awareness of microglia's heterogeneity and plasticity under healthy and pathological conditions.

Spatiotemporal cellular movement and fate decisions during first pharyngeal arch morphogenesis

Cranial neural crest (CNC) cells contribute to different cell types during embryonic development. It is unknown whether postmigratory CNC cells undergo dynamic cellular movement and how the process of cell fate decision occurs within the first pharyngeal arch (FPA). Our investigations demonstrate notable heterogeneity within the CNC cells, refine the patterning domains, and identify progenitor cells within the FPA. These progenitor cells undergo fate bifurcation that separates them into common progenitors and mesenchymal cells, which are characterized by Cdk1 and Spry2/Notch2 expression, respectively. The common progenitors undergo further bifurcations to restrict them into osteogenic/odontogenic and chondrogenic/fibroblast lineages. Disruption of a patterning domain leads to specific mandible and tooth defects, validating the binary cell fate restriction process. Different from the compartment model of mandibular morphogenesis, our data redefine heterogeneous cellular domains within the FPA, reveal dynamic cellular movement in time, and describe a sequential series of binary cell fate decision-making process.

Histone H3.3G34-Mutant Interneuron Progenitors Co-opt PDGFRA for Gliomagenesis

Histone H3.3 glycine 34 to arginine/valine (G34R/V) mutations drive deadly gliomas and show exquisite regional and temporal specificity, suggesting a developmental context permissive to their effects. Here we show that 50% of G34R/V tumors (n = 95) bear activating PDGFRA mutations that display strong selection pressure at recurrence. Although considered gliomas, G34R/V tumors actually arise in GSX2/DLX-expressing interneuron progenitors, where G34R/V mutations impair neuronal differentiation. The lineage of origin may facilitate PDGFRA co-option through a chromatin loop connecting PDGFRA to GSX2 regulatory elements, promoting PDGFRA overexpression and mutation. At the single-cell level, G34R/V tumors harbor dual neuronal/astroglial identity and lack oligodendroglial programs, actively repressed by GSX2/DLX-mediated cell fate specification. G34R/V may become dispensable for tumor maintenance, whereas mutant-PDGFRA is potently oncogenic. Collectively, our results open novel research avenues in deadly tumors. G34R/V gliomas are neuronal malignancies where interneuron progenitors are stalled in differentiation by G34R/V mutations and malignant gliogenesis is promoted by co-option of a potentially targetable pathway, PDGFRA signaling.

Longitudinal Multi-omics Analyses Identify Responses of Megakaryocytes, Erythroid Cells, and Plasmablasts as Hallmarks of Severe COVID-19

Temporal resolution of cellular features associated with a severe COVID-19 disease trajectory is needed for understanding skewed immune responses and defining predictors of outcome. Here, we performed a longitudinal multi-omics study using a two-center cohort of 14 patients. We analyzed the bulk transcriptome, bulk DNA methylome, and single-cell transcriptome (>358,000 cells, including BCR profiles) of peripheral blood samples harvested from up to 5 time points. Validation was performed in two independent cohorts of COVID-19 patients. Severe COVID-19 was characterized by an increase of proliferating, metabolically hyperactive plasmablasts. Coinciding with critical illness, we also identified an expansion of interferon-activated circulating megakaryocytes and increased erythropoiesis with features of hypoxic signaling. Megakaryocyte- and erythroid-cell-derived co-expression modules were predictive of fatal disease outcome. The study demonstrates broad cellular effects of SARS-CoV-2 infection beyond adaptive immune cells and provides an entry point toward developing biomarkers and targeted treatments of patients with COVID-19.

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SARS-CoV2 infection elicits dynamic changes of circulating cells in the blood

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Severe COVID-19 is characterized by increased metabolically active plasmablasts

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Elevation of IFN-activated megakaryocytes and erythroid cells in severe COVID-19

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Cell-type-specific expression signatures are associated with a fatal COVID-19 outcome

Parallel Social Information Processing Circuits Are Differentially Impacted in Autism

Parallel processing circuits are thought to dramatically expand the network capabilities of the nervous system. Magnocellular and parvocellular oxytocin neurons have been proposed to subserve two parallel streams of social information processing, which allow a single molecule to encode a diverse array of ethologically distinct behaviors. Here we provide the first comprehensive characterization of magnocellular and parvocellular oxytocin neurons in male mice, validated across anatomical, projection target, electrophysiological, and transcriptional criteria. We next use novel multiple feature selection tools in Fmr1-KO mice to provide direct evidence that normal functioning of the parvocellular but not magnocellular oxytocin pathway is required for autism-relevant social reward behavior. Finally, we demonstrate that autism risk genes are enriched in parvocellular compared with magnocellular oxytocin neurons. Taken together, these results provide the first evidence that oxytocin-pathway-specific pathogenic mechanisms account for social impairments across a broad range of autism etiologies.

Distinct regional ontogeny and activation of tumor associated macrophages in human glioblastoma

Tumor-associated macrophages (TAMs) constitute up to 50% of tumor bulk in glioblastoma (GBM) and play an important role in tumor maintenance and progression. The recently discovered differences between invading tumour periphery and hypoxic tumor core implies that macrophage biology is also distinct by location. This may provide further insight into the observed treatment resistance to immune modulation. We hypothesize that macrophage activation occurs through processes that are distinct in tumor periphery versus core. We therefore investigated regional differences in TAM recruitment and evolution in GBM by combining open source single cell and bulk gene expression data. We used single cell gene expression data from 4 glioblastomas (total of 3589 cells) and 122 total bulk samples obtained from 10 different patients. Cell identity, ontogeny (bone-marrow derived macrophages-BMDM vs microglia), and macrophage activation state were inferred using verified gene expression signatures. We captured the spectrum of immune states using cell trajectory analysis with pseudotime ordering. In keeping with previous studies, TAMs carrying BMDM identity were more abundant in tumor bulk while microglia-derived TAMs dominated the tumor periphery across all macrophage activation states including pre-activation. We note that core TAMs evolve towards a pro-inflammatory state and identify a subpopulation of cells based on a gene program exhibiting strong, opposing correlation with Programmed cell Death-1 (PD-1) signaling, which may correlate to their response to PD-1 inhibition. By contrast, peripheral TAMs evolve towards anti-inflammatory phenotype and contains a population of cells strongly associated with NFkB signaling. Our preliminary analysis suggests important regional differences in TAMs with regard to recruitment and evolution. We identify regionally distinct and potentially actionable cell subpopulations and advocate the need for a multi-targeted approach to GBM therapeutics.

Reconstructing the Developmental Trajectories of Multiple Subtypes in Pulmonary Parenchymal Epithelial Cells by Single-Cell RNA-seq

Background

Some lung diseases are cell type-specific. It is essential to study the cellular anatomy of the normal human lung for exploring the cellular origin of lung disease and the cell development trajectory.

Methods

We used the Seurat R package for data quality control. The principal component analysis (PCA) was used for linear dimensionality reduction. UMAP and tSNE were used for dimensionality reduction. Muonocle2 was used to extract lung epithelial cells to analyze the subtypes of epithelial cells further and to study the development of these cell subtypes.

Results

We showed a total of 20154 high quality of cells from human normal lung tissue. They were initially divided into 17 clusters cells and then identified as seven types of cells, namely macrophages, monocytes, CD8 + T cells, epithelial cells, endothelial cells, adipocytes, and NK cells. 4240 epithelial cells were extracted for further analysis and they were divided into seven clusters. The seven cell clusters include alveolar cell, alveolar endothelial progenitor, ciliated cell, secretory cell, ionocyte cell, and a group of cells that are not clear at present. We show the development track of these subtypes of epithelial cells, in which we speculate that alveolar epithelial progenitor (AEP) is a kind of progenitor cells that can develop into alveolar cells, and find six essential genes that determine the cell fate, including AGER, RPL10, RPL9, RPS18, RPS27, and SFTPB.

Conclusion

We provide a transcription map of human lung cells, especially the in-depth study on the development of epithelial cell subtypes, which will help us to study lung cell biology and lung diseases.

Statistical significance of cluster membership for unsupervised evaluation of cell identities

MOTIVATION

Single-cell RNA-sequencing (scRNA-seq) allows us to dissect transcriptional heterogeneity arising from cellular types, spatio-temporal contexts and environmental stimuli. Transcriptional heterogeneity may reflect phenotypes and molecular signatures that are often unmeasured or unknown a priori. Cell identities of samples derived from heterogeneous subpopulations are then determined by clustering of scRNA-seq data. These cell identities are used in downstream analyses. How can we examine if cell identities are accurately inferred? Unlike external measurements or labels for single cells, using clustering-based cell identities result in spurious signals and false discoveries.

RESULTS

We introduce non-parametric methods to evaluate cell identities by testing cluster memberships in an unsupervised manner. Diverse simulation studies demonstrate accuracy of the jackstraw test for cluster membership. We propose a posterior probability that a cell should be included in that clustering-based subpopulation. Posterior inclusion probabilities (PIPs) for cluster memberships can be used to select and visualize samples relevant to subpopulations. The proposed methods are applied on three scRNA-seq datasets. First, a mixture of Jurkat and 293T cell lines provides two distinct cellular populations. Second, Cell Hashing yields cell identities corresponding to eight donors which are independently analyzed by the jackstraw. Third, peripheral blood mononuclear cells are used to explore heterogeneous immune populations. The proposed P-values and PIPs lead to probabilistic feature selection of single cells that can be visualized using principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE) and others. By learning uncertainty in clustering high-dimensional data, the proposed methods enable unsupervised evaluation of cluster membership.

AVAILABILITY AND IMPLEMENTATION

https://cran.r-project.org/package=jackstraw.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Global Absence and Targeting of Protective Immune States in Severe COVID-19

While SARS-CoV-2 infection has pleiotropic and systemic effects in some patients, many others experience milder symptoms. We sought a holistic understanding of the severe/mild distinction in COVID-19 pathology, and its origins. We performed a whole-blood preserving single-cell analysis protocol to integrate contributions from all major cell types including neutrophils, monocytes, platelets, lymphocytes and the contents of serum. Patients with mild COVID-19 disease display a coordinated pattern of interferon-stimulated gene (ISG) expression across every cell population and these cells are systemically absent in patients with severe disease. Severe COVID-19 patients also paradoxically produce very high anti-SARS-CoV-2 antibody titers and have lower viral load as compared to mild disease. Examination of the serum from severe patients demonstrates that they uniquely produce antibodies with multiple patterns of specificity against interferon-stimulated cells and that those antibodies functionally block the production of the mild disease-associated ISG-expressing cells. Overzealous and auto-directed antibody responses pit the immune system against itself in many COVID-19 patients and this defines targets for immunotherapies to allow immune systems to provide viral defense.

One Sentence Summary

In severe COVID-19 patients, the immune system fails to generate cells that define mild disease; antibodies in their serum actively prevents the successful production of those cells.

Limiting Self-Renewal of the Basal Compartment by PKA Activation Induces Differentiation and Alters the Evolution of Mammary Tumors

Differentiation therapy utilizes our understanding of the hierarchy of cellular systems to pharmacologically induce a shift toward terminal commitment. While this approach has been a paradigm in treating certain hematological malignancies, efforts to translate this success to solid tumors have met with limited success. Mammary-specific activation of PKA in mouse models leads to aberrant differentiation and diminished self-renewing potential of the basal compartment, which harbors mammary repopulating cells. PKA activation results in tumors that are more benign, exhibiting reduced metastatic propensity, loss of tumor-initiating potential, and increased sensitivity to chemotherapy. Analysis of tumor histopathology revealed features of overt differentiation with papillary characteristics. Longitudinal single-cell profiling at the hyperplasia and tumor stages uncovered an altered path of tumor evolution whereby PKA curtails the emergence of aggressive subpopulations. Acting through the repression of SOX4, PKA activation promotes tumor differentiation and represents a possible adjuvant to chemotherapy for certain breast cancers.

Identification of Differential Gene Groups From Single-Cell Transcriptomes Using Network Entropy

A complex tissue contains a variety of cells with distinct molecular signatures. Single-cell RNA sequencing has characterized the transcriptomes of different cell types and enables researchers to discover the underlying mechanisms of cellular heterogeneity. A critical task in single-cell transcriptome studies is to uncover transcriptional differences among specific cell types. However, the intercellular transcriptional variation is usually confounded with high level of technical noise, which masks the important biological signals. Here, we propose a new computational method DiffGE for differential analysis, adopting network entropy to measure the expression dynamics of gene groups among different cell types and to identify the highly differential gene groups. To evaluate the effectiveness of our proposed method, DiffGE is applied to three independent single-cell RNA-seq datasets and to identify the highly dynamic gene groups that exhibit distinctive expression patterns in different cell types. We compare the results of our method with those of three widely applied algorithms. Further, the gene function analysis indicates that these detected differential gene groups are significantly related to cellular regulation processes. The results demonstrate the power of our method in evaluating the transcriptional dynamics and identifying highly differential gene groups among different cell types.

Developmental, cellular, and behavioral phenotypes in a mouse model of congenital hypoplasia of the dentate gyrus

In the hippocampus, a widely accepted model posits that the dentate gyrus improves learning and memory by enhancing discrimination between inputs. To test this model, we studied conditional knockout mice in which the vast majority of dentate granule cells (DGCs) fail to develop - including nearly all DGCs in the dorsal hippocampus - secondary to eliminating Wntless (Wls) in a subset of cortical progenitors with Gfap-Cre. Other cells in the Wlsfl/-;Gfap-Cre hippocampus were minimally affected, as determined by single nucleus RNA sequencing. CA3 pyramidal cells, the targets of DGC-derived mossy fibers, exhibited normal morphologies with a small reduction in the numbers of synaptic spines. Wlsfl/-;Gfap-Cre mice have a modest performance decrement in several complex spatial tasks, including active place avoidance. They were also modestly impaired in one simpler spatial task, finding a visible platform in the Morris water maze. These experiments support a role for DGCs in enhancing spatial learning and memory.

IRIS3: integrated cell-type-specific regulon inference server from single-cell RNA-Seq

A group of genes controlled as a unit, usually by the same repressor or activator gene, is known as a regulon. The ability to identify active regulons within a specific cell type, i.e., cell-type-specific regulons (CTSR), provides an extraordinary opportunity to pinpoint crucial regulators and target genes responsible for complex diseases. However, the identification of CTSRs from single-cell RNA-Seq (scRNA-Seq) data is computationally challenging. We introduce IRIS3, the first-of-its-kind web server for CTSR inference from scRNA-Seq data for human and mouse. IRIS3 is an easy-to-use server empowered by over 20 functionalities to support comprehensive interpretations and graphical visualizations of identified CTSRs. CTSR data can be used to reliably characterize and distinguish the corresponding cell type from others and can be combined with other computational or experimental analyses for biomedical studies. CTSRs can, therefore, aid in the discovery of major regulatory mechanisms and allow reliable constructions of global transcriptional regulation networks encoded in a specific cell type. The broader impact of IRIS3 includes, but is not limited to, investigation of complex diseases hierarchies and heterogeneity, causal gene regulatory network construction, and drug development. IRIS3 is freely accessible from https://bmbl.bmi.osumc.edu/iris3/ with no login requirement.

Single-cell RNA sequencing of Tocilizumab-treated peripheral blood mononuclear cells as an in vitro model of inflammation

COVID-19 has posed a significant threat to global health. Early data has revealed that IL-6, a key regulatory cytokine, plays an important role in the cytokine storm of COVID-19. Multiple trials are therefore looking at the effects of Tocilizumab, an IL-6 receptor antibody that inhibits IL-6 activity, on treatment of COVID-19, with promising findings. As part of a clinical trial looking at the effects of Tocilizumab treatment on kidney transplant recipients with subclinical rejection, we performed single-cell RNA sequencing of comparing stimulated PBMCs before and after Tocilizumab treatment. We leveraged this data to create an in vitro cytokine storm model, to better understand the effects of Tocilizumab in the presence of inflammation. Tocilizumab-treated cells had reduced expression of inflammatory-mediated genes and biologic pathways, particularly amongst monocytes. These results support the hypothesis that Tocilizumab may hinder the cytokine storm of COVID-19, through a demonstration of biologic impact at the single-cell level.

Single-Cell Transcriptome Analysis Reveals Dynamic Cell Populations and Differential Gene Expression Patterns in Control and Aneurysmal Human Aortic Tissue

BACKGROUND

Ascending thoracic aortic aneurysm (ATAA) is caused by the progressive weakening and dilatation of the aortic wall and can lead to aortic dissection, rupture, and other life-threatening complications. To improve our understanding of ATAA pathogenesis, we aimed to comprehensively characterize the cellular composition of the ascending aortic wall and to identify molecular alterations in each cell population of human ATAA tissues.

METHODS

We performed single-cell RNA sequencing analysis of ascending aortic tissues from 11 study participants, including 8 patients with ATAA (4 women and 4 men) and 3 control subjects (2 women and 1 man). Cells extracted from aortic tissue were analyzed and categorized with single-cell RNA sequencing data to perform cluster identification. ATAA-related changes were then examined by comparing the proportions of each cell type and the gene expression profiles between ATAA and control tissues. We also examined which genes may be critical for ATAA by performing the integrative analysis of our single-cell RNA sequencing data with publicly available data from genome-wide association studies.

RESULTS

We identified 11 major cell types in human ascending aortic tissue; the high-resolution reclustering of these cells further divided them into 40 subtypes. Multiple subtypes were observed for smooth muscle cells, macrophages, and T lymphocytes, suggesting that these cells have multiple functional populations in the aortic wall. In general, ATAA tissues had fewer nonimmune cells and more immune cells, especially T lymphocytes, than control tissues did. Differential gene expression data suggested the presence of extensive mitochondrial dysfunction in ATAA tissues. In addition, integrative analysis of our single-cell RNA sequencing data with public genome-wide association study data and promoter capture Hi-C data suggested that the erythroblast transformation-specific related gene(ERG) exerts an important role in maintaining normal aortic wall function.

CONCLUSIONS

Our study provides a comprehensive evaluation of the cellular composition of the ascending aortic wall and reveals how the gene expression landscape is altered in human ATAA tissue. The information from this study makes important contributions to our understanding of ATAA formation and progression.

The Msi1-mTOR pathway drives the pathogenesis of mammary and extramammary Paget's disease

Mammary and extramammary Paget's Diseases (PD) are a malignant skin cancer characterized by the appearance of Paget cells. Although easily diagnosed, its pathogenesis remains unknown. Here, single-cell RNA-sequencing identified distinct cellular states, novel biomarkers, and signaling pathways - including mTOR, associated with extramammary PD. Interestingly, we identified MSI1 ectopic overexpression in basal epithelial cells of human PD skin, and show that Msi1 overexpression in the epidermal basal layer of mice phenocopies human PD at histopathological, single-cell and molecular levels. Using this mouse model, we identified novel biomarkers of Paget-like cells that translated to human Paget cells. Furthermore, single-cell trajectory, RNA velocity and lineage-tracing analyses revealed a putative keratinocyte-to-Paget-like cell conversion, supporting the in situ transformation theory of disease pathogenesis. Mechanistically, the Msi1-mTOR pathway drives keratinocyte-Paget-like cell conversion, and suppression of mTOR signaling with Rapamycin significantly rescued the Paget-like phenotype in Msi1-overexpressing transgenic mice. Topical Rapamycin treatment improved extramammary PD-associated symptoms in humans, suggesting mTOR inhibition as a novel therapeutic treatment in PD.

Towards systems tissue engineering: Elucidating the dynamics, spatial coordination, and individual cells driving emergent behaviors

Biomaterial systems have enabled the in vitro production of complex, emergent tissue behaviors that were not possible with conventional two-dimensional culture systems, allowing for analysis of both normal development and disease processes. We propose that the path towards developing the design parameters for biomaterial systems lies with identifying the molecular drivers of emergent behavior through leveraging technological advances in systems biology, including single cell omics, genetic engineering, and high content imaging. This growing research opportunity at the intersection of the fields of tissue engineering and systems biology - systems tissue engineering - can uniquely interrogate the mechanisms by which complex tissue behaviors emerge with the potential to capture the contribution of i) dynamic regulation of tissue development and dysregulation, ii) single cell heterogeneity and the function of rare cell types, and iii) the spatial distribution and structure of individual cells and cell types within a tissue. By leveraging advances in both biological and materials data science, systems tissue engineering can facilitate the identification of biomaterial design parameters that will accelerate basic science discovery and translation.

APOE and TREM2 regulate amyloid-responsive microglia in Alzheimer's disease

Beta-amyloid deposition is a defining feature of Alzheimer's disease (AD). How genetic risk factors, like APOE and TREM2, intersect with cellular responses to beta-amyloid in human tissues is not fully understood. Using single-nucleus RNA sequencing of postmortem human brain with varied APOE and TREM2 genotypes and neuropathology, we identified distinct microglia subpopulations, including a subpopulation of CD163-positive amyloid-responsive microglia (ARM) that are depleted in cases with APOE and TREM2 risk variants. We validated our single-nucleus RNA sequencing findings in an expanded cohort of AD cases, demonstrating that APOE and TREM2 risk variants are associated with a significant reduction in CD163-positive amyloid-responsive microglia. Our results showcase the diverse microglial response in AD and underscore how genetic risk factors influence cellular responses to underlying pathologies.

Naught all zeros in sequence count data are the same

Genomic studies feature multivariate count data from high-throughput DNA sequencing experiments, which often contain many zero values. These zeros can cause artifacts for statistical analyses and multiple modeling approaches have been developed in response. Here, we apply different zero-handling models to gene-expression and microbiome datasets and show models can disagree substantially in terms of identifying the most differentially expressed sequences. Next, to rationally examine how different zero handling models behave, we developed a conceptual framework outlining four types of processes that may give rise to zero values in sequence count data. Last, we performed simulations to test how zero handling models behave in the presence of these different zero generating processes. Our simulations showed that simple count models are sufficient across multiple processes, even when the true underlying process is unknown. On the other hand, a common zero handling technique known as "zero-inflation" was only suitable under a zero generating process associated with an unlikely set of biological and experimental conditions. In concert, our work here suggests several specific guidelines for developing and choosing state-of-the-art models for analyzing sparse sequence count data.

What has single-cell RNA-seq taught us about mammalian spermatogenesis?

Mammalian spermatogenesis is a complex developmental program that transforms mitotic testicular germ cells (spermatogonia) into mature male gametes (sperm) for production of offspring. For decades, it has been known that this several-weeks-long process involves a series of highly ordered and morphologically recognizable cellular changes as spermatogonia proliferate, spermatocytes undertake meiosis, and spermatids develop condensed nuclei, acrosomes, and flagella. Yet, much of the underlying molecular logic driving these processes has remained opaque because conventional characterization strategies often aggregated groups of cells to meet technical requirements or due to limited capability for cell selection. Recently, a cornucopia of single-cell transcriptome studies has begun to lift the veil on the full compendium of gene expression phenotypes and changes underlying spermatogenic development. These datasets have revealed the previously obscured molecular heterogeneity among and between varied spermatogenic cell types and are reinvigorating investigation of testicular biology. This review describes the extent of available single-cell RNA-seq profiles of spermatogenic and testicular somatic cells, how those data were produced and evaluated, their present value for advancing knowledge of spermatogenesis, and their potential future utility at both the benchtop and bedside.

The myeloid type I interferon response to myocardial infarction begins in bone marrow and is regulated by Nrf2-activated macrophages

Sterile tissue injury is thought to locally activate innate immune responses via damage-associated molecular patterns (DAMPs). Whether innate immune pathways are remotely activated remains relatively unexplored. Here, by analyzing ~145,000 single-cell transcriptomes at steady state and after myocardial infarction (MI) in mice and humans, we show that the type I interferon (IFN) response, characterized by expression of IFN-stimulated genes (ISGs), begins far from the site of injury, in neutrophil and monocyte progenitors within the bone marrow. In the peripheral blood of patients, we observed defined subsets of ISG-expressing neutrophils and monocytes. In the bone marrow and blood of mice, ISG expression was detected in neutrophils and monocytes and their progenitors, intensified with maturation at steady-state and after MI, and was controlled by Tet2 and Irf3 transcriptional regulators. Within the infarcted heart, ISG-expressing cells were negatively regulated by Nrf2 activation in Ccr2^- steady-state cardiac macrophages. Our results show that IFN signaling begins in the bone marrow, implicate multiple transcriptional regulators (Tet2, Irf3, and Nrf2) in governing ISG expression, and provide a clinical biomarker (ISG score) for studying IFN signaling in patients.