Trajectory-based differential expression analysis for single-cell sequencing data

Updated skin transcriptomic atlas depicted by reciprocal contribution of single-nucleus RNA sequencing and single-cell RNA sequencing

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) has advanced our understanding of skin biology, but its utility is restricted by the requirement of fresh samples, inadequate dissociation-induced cell loss or death, and activation during tissue digestion. Single-nucleus RNA sequencing (snRNA-seq) can use frozen, hard-to-dissociate materials, which might be a promising method to circumvent the limitations of scRNA-seq for the skin tissue.

OBJECTIVE

To profile skin cells using snRNA-seq in parallel with scRNA-seq.

METHODS

We performed snRNA-seq in parallel with scRNA-seq for the bisected skin sample of one person and integrated previously published scRNA-seq data for analysis. We comparatively analyzed the differences in cell proportions and gene expression between the two methods. The differentiation trajectories of keratinocytes and fibroblasts were analyzed by Slingshot analysis.

RESULTS

snRNA-seq was less susceptible to contamination from mitochondrial and ribosomal RNA, and exhibited a greater capacity to detect transcription factors. snRNA-seq identified more spatially and functionally relevant keratinocyte clusters that constitute cell trajectories with expected differentiation dynamics. Novel markers, e.g., LYPD3, EMP2, and CSTB, were revealed for different differentiation stages of keratinocytes, and NFIB and GRHL1 were identified as transcription factors involving in the proliferation and functional differentiation of keratinocytes. Fibroblasts were found in a state of activation in scRNA-seq. And scRNA-seq detected a greater number of immune cells.

CONCLUSIONS

We generated an updated atlas of the skin transcriptome based on the reciprocal contribution of scRNA-seq and snRNA-seq.

Schwann cells regulate tumor cells and cancer-associated fibroblasts in the pancreatic ductal adenocarcinoma microenvironment

Neuropathy is a feature more frequently observed in pancreatic ductal adenocarcinoma (PDAC) than other tumors. Schwann cells, the most prevalent cell type in peripheral nerves, migrate toward tumor cells and associate with poor prognosis in PDAC. To unveil the effects of Schwann cells on the neuro-stroma niche, here we perform single-cell RNA-sequencing and microarray-based spatial transcriptome analysis of PDAC tissues. Results suggest that Schwann cells may drive tumor cells and cancer-associated fibroblasts (CAFs) to more malignant subtypes: basal-like and inflammatory CAFs (iCAFs), respectively. Moreover, in vitro and in vivo assays demonstrate that Schwann cells enhance the proliferation and migration of PDAC cells via Midkine signaling and promote the switch of CAFs to iCAFs via interleukin-1α. Culture of tumor cells and CAFs with Schwann cells conditioned medium accelerates PDAC progression. Thus, we reveal that Schwann cells induce malignant subtypes of tumor cells and CAFs in the PDAC milieu.

Autism-linked UBE3A gain-of-function mutation causes interneuron and behavioral phenotypes when inherited maternally or paternally in mice

The E3 ubiquitin ligase Ube3a is biallelically expressed in neural progenitors and glial cells, suggesting that UBE3A gain-of-function mutations might cause neurodevelopmental disorders irrespective of parent of origin. Here, we engineered a mouse line that harbors an autism-linked UBE3AT485A (T503A in mouse) gain-of-function mutation and evaluated phenotypes in animals that inherited the mutant allele paternally, maternally, or from both parents. We find that paternally and maternally expressed UBE3AT503A results in elevated UBE3A activity in neural progenitors and glial cells. Expression of UBE3AT503A from the maternal allele, but not the paternal one, leads to a persistent elevation of UBE3A activity in neurons. Mutant mice display behavioral phenotypes that differ by parent of origin. Expression of UBE3AT503A, irrespective of its parent of origin, promotes transient embryonic expansion of Zcchc12 lineage interneurons. Phenotypes of Ube3aT503A mice are distinct from Angelman syndrome model mice. Our study has clinical implications for a growing number of disease-linked UBE3A gain-of-function mutations.

Decreased left heart flow in fetal lambs causes left heart hypoplasia and pro-fibrotic tissue remodeling

Low blood flow through the fetal left heart is often conjectured as an etiology for hypoplastic left heart syndrome (HLHS). To investigate if a decrease in left heart flow results in growth failure, we generate left ventricular inflow obstruction (LVIO) in mid-gestation fetal lambs by implanting coils in their left atrium using an ultrasound-guided percutaneous technique. Significant LVIO recapitulates important clinical features of HLHS: decreased antegrade aortic valve flow, compensatory retrograde perfusion of the brain and ascending aorta (AAo) from the arterial duct, severe left heart hypoplasia, a non-apex forming LV, and a thickened endocardial layer. The hypoplastic AAo have miRNA-gene pairs annotating to cell proliferation that are inversely differentially expressed by bulk RNA-seq. Single-nucleus RNA-seq of the hypoplastic LV myocardium shows an increase in fibroblasts with a reciprocal decrease in cardiomyocyte nuclei proportions. Fibroblasts, cardiomyocytes and endothelial cells from hypoplastic myocardium have increased expression of extracellular matrix component or fibrosis genes with dysregulated fibroblast growth factor signaling. Hence, a severe sustained ( ~ 1/3 gestation) reduction in fetal left heart flow is sufficient to cause left heart hypoplasia. This is accompanied by changes in cellular composition and gene expression consistent with a pro-fibrotic environment and aberrant induction of mesenchymal programs.

TCDD dysregulation of lncRNA expression, liver zonation and intercellular communication across the liver lobule

The persistent environmental aryl hydrocarbon receptor agonist and hepatotoxin TCDD (2,3,7,8-tetrachlorodibenzo-p-dioxin) induces hepatic lipid accumulation (steatosis), inflammation (steatohepatitis) and fibrosis. Thousands of liver-expressed, nuclear-localized lncRNAs with regulatory potential have been identified; however, their roles in TCDD-induced hepatoxicity and liver disease are unknown. We analyzed single nucleus (sn)RNA-seq data from control and subchronic (4 wk) TCDD-exposed mouse liver to determine liver cell-type specificity, zonation and differential expression profiles for thousands of lncRNAs. TCDD dysregulated >4000 of these lncRNAs in one or more liver cell types, including 684 lncRNAs specifically dysregulated in liver non-parenchymal cells. Trajectory inference analysis revealed major disruption by TCDD of hepatocyte zonation, affecting >800 genes, including 121 lncRNAs, with strong enrichment for lipid metabolism genes. TCDD also dysregulated expression of >200 transcription factors, including 19 Nuclear Receptors, most notably in hepatocytes and Kupffer cells. TCDD-induced changes in cell-cell communication patterns included marked decreases in EGF signaling from hepatocytes to non-parenchymal cells and increases in extracellular matrix-receptor interactions central to liver fibrosis. Gene regulatory networks constructed from the snRNA-seq data identified TCDD-exposed liver network-essential lncRNA regulators linked to functions such as fatty acid metabolic process, peroxisome and xenobiotic metabolism. Networks were validated by the striking enrichments that predicted regulatory lncRNAs showed for specific biological pathways. These findings highlight the power of snRNA-seq to discover functional roles for many xenobiotic-responsive lncRNAs in both hepatocytes and liver non-parenchymal cells and to elucidate novel aspects of foreign chemical-induced hepatotoxicity and liver disease, including dysregulation of intercellular communication within the liver lobule.

Therapeutic Potential of PTB Inhibition Through Converting Glial Cells to Neurons in the Brain

Cell replacement therapy represents a promising approach for treating neurodegenerative diseases. Contrary to the common addition strategy to generate new neurons from glia by overexpressing a lineage-specific transcription factor(s), a recent study introduced a subtraction strategy by depleting a single RNA-binding protein, Ptbp1, to convert astroglia to neurons not only in vitro but also in the brain. Given its simplicity, multiple groups have attempted to validate and extend this attractive approach but have met with difficulty in lineage tracing newly induced neurons from mature astrocytes, raising the possibility of neuronal leakage as an alternative explanation for apparent astrocyte-to-neuron conversion. This review focuses on the debate over this critical issue. Importantly, multiple lines of evidence suggest that Ptbp1 depletion can convert a selective subpopulation of glial cells into neurons and, via this and other mechanisms, reverse deficits in a Parkinson's disease model, emphasizing the importance of future efforts in exploring this therapeutic strategy.

Single cell susceptibility to SARS-CoV-2 infection is driven by variable cell states

The ability of a virus to infect a cell type is at least in part determined by the presence of host factors required for the viral life cycle. However, even within cell types that express known factors needed for infection, not every cell is equally susceptible, suggesting that our knowledge of the full spectrum of factors that promote infection is incomplete. Profiling the most susceptible subsets of cells within a population may reveal additional factors that promote infection. However, because viral infection dramatically alters the state of the cell, new approaches are needed to reveal the state of these cells prior to infection with virus. Here, we used single-cell clone tracing to retrospectively identify and characterize lung epithelial cells that are highly susceptible to infection with SARS-CoV-2. The transcriptional state of these highly susceptible cells includes markers of retinoic acid signaling and epithelial differentiation. Loss of candidate factors identified by our approach revealed that many of these factors play roles in viral entry. Moreover, a subset of these factors exert control over the infectable cell state itself, regulating the expression of key factors associated with viral infection and entry. Analysis of patient samples revealed the heterogeneous expression of these factors across both cells and patients in vivo. Further, the expression of these factors is upregulated in particular inflammatory pathologies. Altogether, our results show that the variable expression of intrinsic cell states is a major determinant of whether a cell can be infected by SARS-CoV-2.

TET2 and TET3 loss disrupts small intestine differentiation and homeostasis

TET2/3 play a well-known role in epigenetic regulation and mouse development. However, their function in cellular differentiation and tissue homeostasis remains poorly understood. Here we show that ablation of TET2/3 in intestinal epithelial cells results in a murine phenotype characterized by a severe homeostasis imbalance in the small intestine. Tet2/3-deleted mice show a pronounced loss of mature Paneth cells as well as fewer Tuft and more Enteroendocrine cells. Further results show major changes in DNA methylation at putative enhancers, which are associated with cell fate-determining transcription factors and functional effector genes. Notably, pharmacological inhibition of DNA methylation partially rescues the methylation and cellular defects. TET2/3 loss also alters the microbiome, predisposing the intestine to inflammation under homeostatic conditions and acute inflammation-induced death. Together, our results uncover previously unrecognized critical roles for DNA demethylation, possibly occurring subsequently to chromatin opening during intestinal development, culminating in the establishment of normal intestinal crypts.

Old and newly synthesized histones are asymmetrically distributed in Drosophila intestinal stem cell divisions

We report that preexisting (old) and newly synthesized (new) histones H3 and H4 are asymmetrically partitioned during the division of Drosophila intestinal stem cells (ISCs). Furthermore, the inheritance patterns of old and new H3 and H4 in postmitotic cell pairs correlate with distinct expression patterns of Delta, an important cell fate gene. To understand the biological significance of this phenomenon, we expressed a mutant H3T3A to compromise asymmetric histone inheritance. Under this condition, we observe an increase in Delta-symmetric cell pairs and overpopulated ISC-like, Delta-positive cells. Single-cell RNA-seq assays further indicate that H3T3A expression compromises ISC differentiation. Together, our results indicate that asymmetric histone inheritance potentially contributes to establishing distinct cell identities in a somatic stem cell lineage, consistent with previous findings in Drosophila male germline stem cells.

Dysregulation of murine long noncoding single-cell transcriptome in nonalcoholic steatohepatitis and liver fibrosis

LncRNAs comprise a heterogeneous class of RNA-encoding genes typified by low expression, nuclear enrichment, high tissue-specificity, and functional diversity, but the vast majority remain uncharacterized. Here, we assembled the mouse liver noncoding transcriptome from >2000 bulk RNA-seq samples and discovered 48,261 liver-expressed lncRNAs, a majority novel. Using these lncRNAs as a single-cell transcriptomic reference set, we elucidated lncRNA dysregulation in mouse models of high fat diet-induced nonalcoholic steatohepatitis and carbon tetrachloride-induced liver fibrosis. Trajectory inference analysis revealed lncRNA zonation patterns across the liver lobule in each major liver cell population. Perturbations in lncRNA expression and zonation were common in several disease-associated liver cell types, including nonalcoholic steatohepatitis-associated macrophages, a hallmark of fatty liver disease progression, and collagen-producing myofibroblasts, a central feature of liver fibrosis. Single-cell-based gene regulatory network analysis using bigSCale2 linked individual lncRNAs to specific biological pathways, and network-essential regulatory lncRNAs with disease-associated functions were identified by their high network centrality metrics. For a subset of these lncRNAs, promoter sequences of the network-defined lncRNA target genes were significantly enriched for lncRNA triplex formation, providing independent mechanistic support for the lncRNA-target gene linkages predicted by the gene regulatory networks. These findings elucidate liver lncRNA cell-type specificities, spatial zonation patterns, associated regulatory networks, and temporal patterns of dysregulation during hepatic disease progression. A subset of the liver disease-associated regulatory lncRNAs identified have human orthologs and are promising candidates for biomarkers and therapeutic targets.

Defining blood-induced microglia functions in neurodegeneration through multiomic profiling

Blood protein extravasation through a disrupted blood-brain barrier and innate immune activation are hallmarks of neurological diseases and emerging therapeutic targets. However, how blood proteins polarize innate immune cells remains largely unknown. Here, we established an unbiased blood-innate immunity multiomic and genetic loss-of-function pipeline to define the transcriptome and global phosphoproteome of blood-induced innate immune polarization and its role in microglia neurotoxicity. Blood induced widespread microglial transcriptional changes, including changes involving oxidative stress and neurodegenerative genes. Comparative functional multiomics showed that blood proteins induce distinct receptor-mediated transcriptional programs in microglia and macrophages, such as redox, type I interferon and lymphocyte recruitment. Deletion of the blood coagulation factor fibrinogen largely reversed blood-induced microglia neurodegenerative signatures. Genetic elimination of the fibrinogen-binding motif to CD11b in Alzheimer's disease mice reduced microglial lipid metabolism and neurodegenerative signatures that were shared with autoimmune-driven neuroinflammation in multiple sclerosis mice. Our data provide an interactive resource for investigation of the immunology of blood proteins that could support therapeutic targeting of microglia activation by immune and vascular signals.

Assessing the influence of distinct culture media on human pre-implantation development using single-embryo transcriptomics

The use of assisted reproductive technologies is consistently rising across the world. However, making an informed choice on which embryo culture medium should be preferred to ensure satisfactory pregnancy rates and the health of future children critically lacks scientific background. In particular, embryos within their first days of development are highly sensitive to their micro-environment, and it is unknown how their transcriptome adapts to different embryo culture compositions. Here, we determined the impact of culture media composition on gene expression in human pre-implantation embryos. By employing single-embryo RNA-sequencing after 2 or 5 days of the post-fertilization culture in different commercially available media (Ferticult, Global, and SSM), we revealed medium-specific differences in gene expression changes. Embryos cultured pre-compaction until day 2 in Ferticult or Global media notably displayed 266 differentially expressed genes, which were related to essential developmental pathways. Herein, 19 of them could have a key role in early development, based on their previously described dynamic expression changes across development. When embryos were cultured after day 2 in the same media considered more suitable because of its amino acid enrichment, 18 differentially expressed genes thought to be involved in the transition from early to later embryonic stages were identified. Overall, the differences were reduced at the blastocyst stage, highlighting the ability of embryos conceived in a suboptimal in vitro culture medium to mitigate the transcriptomic profile acquired under different pre-compaction environments.

CD168+ macrophages promote hepatocellular carcinoma tumor stemness and progression through TOP2A/β-catenin/YAP1 axis

Liver cancer stem-like cells (LCSCs) are the main cause of heterogeneity and poor prognosis in hepatocellular carcinoma (HCC). In this study, we aimed to explore the origin of LCSCs and the role of the TOP2A/β-catenin/YAP1 axis in tumor stemness and progression. Using single-cell RNA-seq analysis, we identified TOP2A+CENPF+ LCSCs, which were mainly regulated by CD168+ M2-like macrophages. Furthermore, spatial location analysis and fluorescent staining confirmed that LCSCs were enriched at tumor margins, constituting the spatial heterogeneity of HCC. Mechanistically, TOP2A competitively binds to β-catenin, leading to disassociation of β-catenin from YAP1, promoting HCC stemness and overgrowth. Our study provides valuable insights into the spatial transcriptome heterogeneity of the HCC microenvironment and the critical role of TOP2A/β-catenin/YAP1 axis in HCC stemness and progression.

Aging disrupts gene expression timing during muscle regeneration

Skeletal muscle function and regenerative capacity decline during aging, yet factors driving these changes are incompletely understood. Muscle regeneration requires temporally coordinated transcriptional programs to drive myogenic stem cells to activate, proliferate, fuse to form myofibers, and to mature as myonuclei, restoring muscle function after injury. We assessed global changes in myogenic transcription programs distinguishing muscle regeneration in aged mice from young mice by comparing pseudotime trajectories from single-nucleus RNA sequencing of myogenic nuclei. Aging-specific differences in coordinating myogenic transcription programs necessary for restoring muscle function occur following muscle injury, likely contributing to compromised regeneration in aged mice. Differences in pseudotime alignment of myogenic nuclei when comparing aged with young mice via dynamic time warping revealed pseudotemporal differences becoming progressively more severe as regeneration proceeds. Disruptions in timing of myogenic gene expression programs may contribute to incomplete skeletal muscle regeneration and declines in muscle function as organisms age.

Single-Cell Transcriptome Analysis Identifies Subclusters with Inflammatory Fibroblast Responses in Localized Scleroderma

Localized scleroderma (LS) is an autoimmune disease with both inflammatory and fibrotic components causing an abnormal deposition of collagen in the skin and underlying tissue, often leading to disfigurement and disability. Much of its pathophysiology is extrapolated from systemic sclerosis (SSc) since the histopathology findings in the skin are nearly identical. However, LS is critically understudied. Single-cell RNA sequencing (scRNA seq) technology provides a novel way to obtain detailed information at the individual cellular level, overcoming this barrier. Here, we analyzed the affected skin of 14 patients with LS (pediatric and adult) and 14 healthy controls. Fibroblast populations were the focus, since they are the main drivers of fibrosis in SSc. We identified 12 fibroblast subclusters in LS, which overall had an inflammatory gene expression (IFN and HLA-associated genes). A myofibroblast-like cluster (SFRP4/PRSS23) was more prevalent in LS subjects and shared many upregulated genes expressed in SSc-associated myofibroblasts, though it also had strong expression of CXCL9/10/11, known CXCR3 ligands. A CXCL2/IRF1 cluster identified was unique to LS, with a robust inflammatory gene signature, including IL-6, and according to cell communication analysis are influenced by macrophages. In summary, potential disease-propagating fibroblasts and associated gene signatures were identified in LS skin via scRNA seq.

Single-cell profiling identifies a novel human polyclonal unconventional T cell lineage

In the human thymus, a CD10+ PD-1+ TCRαβ+ differentiation pathway diverges from the conventional single positive T cell lineages at the early double-positive stage. Here, we identify the progeny of this unconventional lineage in antigen-inexperienced blood. These unconventional T cells (UTCs) in thymus and blood share a transcriptomic profile, characterized by hallmark transcription factors (i.e., ZNF683 and IKZF2), and a polyclonal TCR repertoire with autoreactive features, exhibiting a bias toward early TCRα chain rearrangements. Single-cell RNA sequencing confirms a common developmental trajectory between the thymic and blood UTCs and clearly delineates this unconventional lineage in blood. Besides MME+ recent thymic emigrants, effector-like clusters are identified in this heterogeneous lineage. Expression of Helios and KIR and a decreased CD8β expression are characteristics of this lineage. This UTC lineage could be identified in adult blood and intestinal tissues. In summary, our data provide a comprehensive characterization of the polyclonal unconventional lineage in antigen-inexperienced blood and identify the adult progeny.

CIARA: a cluster-independent algorithm for identifying markers of rare cell types from single-cell sequencing data

A powerful feature of single-cell genomics is the possibility of identifying cell types from their molecular profiles. In particular, identifying novel rare cell types and their marker genes is a key potential of single-cell RNA sequencing. Standard clustering approaches perform well in identifying relatively abundant cell types, but tend to miss rarer cell types. Here, we have developed CIARA (Cluster Independent Algorithm for the identification of markers of RAre cell types), a cluster-independent computational tool designed to select genes that are likely to be markers of rare cell types. Genes selected by CIARA are subsequently integrated with common clustering algorithms to single out groups of rare cell types. CIARA outperforms existing methods for rare cell type detection, and we use it to find previously uncharacterized rare populations of cells in a human gastrula and among mouse embryonic stem cells treated with retinoic acid. Moreover, CIARA can be applied more generally to any type of single-cell omic data, thus allowing the identification of rare cells across multiple data modalities. We provide implementations of CIARA in user-friendly packages available in R and Python.

Single-cell transcriptomics reveals immune suppression and cell states predictive of patient outcomes in rhabdomyosarcoma

Paediatric rhabdomyosarcoma (RMS) is a soft tissue malignancy of mesenchymal origin that is thought to arise as a consequence of derailed myogenic differentiation. Despite intensive treatment regimens, the prognosis for high-risk patients remains dismal. The cellular differentiation states underlying RMS and how these relate to patient outcomes remain largely elusive. Here, we use single-cell mRNA sequencing to generate a transcriptomic atlas of RMS. Analysis of the RMS tumour niche reveals evidence of an immunosuppressive microenvironment. We also identify a putative interaction between NECTIN3 and TIGIT, specific to the more aggressive fusion-positive (FP) RMS subtype, as a potential cause of tumour-induced T-cell dysfunction. In malignant RMS cells, we define transcriptional programs reflective of normal myogenic differentiation and show that these cellular differentiation states are predictive of patient outcomes in both FP RMS and the less aggressive fusion-negative subtype. Our study reveals the potential of therapies targeting the immune microenvironment of RMS and suggests that assessing tumour differentiation states may enable a more refined risk stratification.

Charting a high-resolution roadmap for regeneration of pancreatic β cells by in vivo transdifferentiation from adult acinar cells

Adult mammals have limited capacity to regenerate functional cells. Promisingly, in vivo transdifferentiation heralds the possibility of regeneration by lineage reprogramming from other fully differentiated cells. However, the process of regeneration by in vivo transdifferentiation in mammals is poorly understood. Using pancreatic β cell regeneration as a paradigm, we performed a single-cell transcriptomic study of in vivo transdifferentiation from adult mouse acinar cells to induced β cells. Using unsupervised clustering analysis and lineage trajectory construction, we uncovered that the cell fate remodeling trajectory was linear at the initial stage and the reprogrammed cells either evolved to induced β cells or toward a "dead-end" state after day 4.Moreover, functional analyses identified both p53 and Dnmt3a that acted as reprogramming barriers during the process of in vivo transdifferentiation. Collectively, we decipher a high-resolution roadmap of regeneration by in vivo transdifferentiation and provide a detailed molecular blueprint to facilitate mammalian regeneration.

Cell type specific transcriptomic differences in depression show similar patterns between males and females but implicate distinct cell types and genes

Major depressive disorder (MDD) is a common, heterogenous, and potentially serious psychiatric illness. Diverse brain cell types have been implicated in MDD etiology. Significant sexual differences exist in MDD clinical presentation and outcome, and recent evidence suggests different molecular bases for male and female MDD. We evaluated over 160,000 nuclei from 71 female and male donors, leveraging new and pre-existing single-nucleus RNA-sequencing data from the dorsolateral prefrontal cortex. Cell type specific transcriptome-wide threshold-free MDD-associated gene expression patterns were similar between the sexes, but significant differentially expressed genes (DEGs) diverged. Among 7 broad cell types and 41 clusters evaluated, microglia and parvalbumin interneurons contributed the most DEGs in females, while deep layer excitatory neurons, astrocytes, and oligodendrocyte precursors were the major contributors in males. Further, the Mic1 cluster with 38% of female DEGs and the ExN10_L46 cluster with 53% of male DEGs, stood out in the meta-analysis of both sexes.

Differentiation and single-cell RNA-seq analyses of human pluripotent-stem-cell-derived renal organoids

Here, we present a protocol for the maintenance and differentiation of human pluripotent stem cells into renal organoids. We describe steps for using a series of readily made differentiation media, multiplexed sample single-cell RNA-seq analysis, quality control, and validation of organoids using immunofluorescence. This provides a rapid and reproducible model of human kidney development and renal disease modeling. Finally, we detail genome engineering using CRISPR-Cas9 homology-directed repair for the generation of renal disease models. For complete details on the use and execution of this protocol, please refer to Pietrobon et al.¹.

Ribonucleotide reductase regulatory subunit M2 drives glioblastoma TMZ resistance through modulation of dNTP production

During therapy, adaptations driven by cellular plasticity are partly responsible for driving the inevitable recurrence of glioblastoma (GBM). To investigate plasticity-induced adaptation during standard-of-care chemotherapy temozolomide (TMZ), we performed in vivo single-cell RNA sequencing in patient-derived xenograft (PDX) tumors of GBM before, during, and after therapy. Comparing single-cell transcriptomic patterns identified distinct cellular populations present during TMZ therapy. Of interest was the increased expression of ribonucleotide reductase regulatory subunit M2 (RRM2), which we found to regulate dGTP and dCTP production vital for DNA damage response during TMZ therapy. Furthermore, multidimensional modeling of spatially resolved transcriptomic and metabolomic analysis in patients' tissues revealed strong correlations between RRM2 and dGTP. This supports our data that RRM2 regulates the demand for specific dNTPs during therapy. In addition, treatment with the RRM2 inhibitor 3-AP (Triapine) enhances the efficacy of TMZ therapy in PDX models. We present a previously unidentified understanding of chemoresistance through critical RRM2-mediated nucleotide production.

Feature selection for preserving biological trajectories in single-cell data

Single-cell technologies can readily measure the expression of thousands of molecular features from individual cells undergoing dynamic biological processes, such as cellular differentiation, immune response, and disease progression. While examining cells along a computationally ordered pseudotime offers the potential to study how subtle changes in gene or protein expression impact cell fate decision-making, identifying characteristic features that drive continuous biological processes remains difficult to detect from unenriched and noisy single-cell data. Given that all profiled sources of feature variation contribute to the cell-to-cell distances that define an inferred cellular trajectory, including confounding sources of biological variation (e.g. cell cycle or metabolic state) or noisy and irrelevant features (e.g. measurements with low signal-to-noise ratio) can mask the underlying trajectory of study and hinder inference. Here, we present DELVE (dynamic selection of locally covarying features), an unsupervised feature selection method for identifying a representative subset of dynamically-expressed molecular features that recapitulates cellular trajectories. In contrast to previous work, DELVE uses a bottom-up approach to mitigate the effect of unwanted sources of variation confounding inference, and instead models cell states from dynamic feature modules that constitute core regulatory complexes. Using simulations, single-cell RNA sequencing data, and iterative immunofluorescence imaging data in the context of the cell cycle and cellular differentiation, we demonstrate that DELVE selects features that more accurately characterize cell populations and improve the recovery of cell type transitions. This feature selection framework provides an alternative approach for improving trajectory inference and uncovering co-variation amongst features along a biological trajectory. DELVE is implemented as an open-source python package and is publicly available at: https://github.com/jranek/delve.

Profiling spatiotemporal gene expression of the developing human spinal cord and implications for ependymoma origin

The spatiotemporal regulation of cell fate specification in the human developing spinal cord remains largely unknown. In this study, by performing integrated analysis of single-cell and spatial multi-omics data, we used 16 prenatal human samples to create a comprehensive developmental cell atlas of the spinal cord during post-conceptional weeks 5-12. This revealed how the cell fate commitment of neural progenitor cells and their spatial positioning are spatiotemporally regulated by specific gene sets. We identified unique events in human spinal cord development relative to rodents, including earlier quiescence of active neural stem cells, differential regulation of cell differentiation and distinct spatiotemporal genetic regulation of cell fate choices. In addition, by integrating our atlas with pediatric ependymomas data, we identified specific molecular signatures and lineage-specific genes of cancer stem cells during progression. Thus, we delineate spatiotemporal genetic regulation of human spinal cord development and leverage these data to gain disease insight.

Brassinosteroid gene regulatory networks at cellular resolution in the Arabidopsis root

Brassinosteroids are plant steroid hormones that regulate diverse processes, such as cell division and cell elongation, through gene regulatory networks that vary in space and time. By using time series single-cell RNA sequencing to profile brassinosteroid-responsive gene expression specific to different cell types and developmental stages of the Arabidopsis root, we identified the elongating cortex as a site where brassinosteroids trigger a shift from proliferation to elongation associated with increased expression of cell wall-related genes. Our analysis revealed HOMEOBOX FROM ARABIDOPSIS THALIANA 7 (HAT7) and GT-2-LIKE 1 (GTL1) as brassinosteroid-responsive transcription factors that regulate cortex cell elongation. These results establish the cortex as a site of brassinosteroid-mediated growth and unveil a brassinosteroid signaling network regulating the transition from proliferation to elongation, which illuminates aspects of spatiotemporal hormone responses.

Estimating and Assessing Differential Equation Models with Time-Course Data

Ordinary differential equation (ODE) models are widely used to describe chemical or biological processes. This Article considers the estimation and assessment of such models on the basis of time-course data. Due to experimental limitations, time-course data are often noisy, and some components of the system may not be observed. Furthermore, the computational demands of numerical integration have hindered the widespread adoption of time-course analysis using ODEs. To address these challenges, we explore the efficacy of the recently developed MAGI (MAnifold-constrained Gaussian process Inference) method for ODE inference. First, via a range of examples we show that MAGI is capable of inferring the parameters and system trajectories, including unobserved components, with appropriate uncertainty quantification. Second, we illustrate how MAGI can be used to assess and select different ODE models with time-course data based on MAGI's efficient computation of model predictions. Overall, we believe MAGI is a useful method for the analysis of time-course data in the context of ODE models, which bypasses the need for any numerical integration.

Aging Atlas Reveals Cell-Type-Specific Regulation of Pro-longevity Strategies

Organism aging occurs at the multicellular level; however, how pro-longevity mechanisms slow down aging in different cell types remains unclear. We generated single-cell transcriptomic atlases across the lifespan of Caenorhabditis elegans under different pro-longevity conditions (http://mengwanglab.org/atlas). We found cell-specific, age-related changes across somatic and germ cell types and developed transcriptomic aging clocks for different tissues. These clocks enabled us to determine tissue-specific aging-slowing effects of different pro-longevity mechanisms, and identify major cell types sensitive to these regulations. Additionally, we provided a systemic view of alternative polyadenylation events in different cell types, as well as their cell-type-specific changes during aging and under different pro-longevity conditions. Together, this study provides molecular insights into how aging occurs in different cell types and how they respond to pro-longevity strategies.

Thymus antibody-secreting cells possess an interferon gene signature and are preferentially expanded in young female mice

Antibody-secreting cells (ASCs) are key contributors to humoral immunity through immunoglobulin production and the potential to be long-lived. ASC persistence has been recognized in the autoimmune thymus (THY); however, only recently has this population been appreciated in healthy THY tissue. We showed that the young female THY was skewed toward higher production of ASCs relative to males. However, these differences disappeared with age. In both sexes, THY ASCs included Ki-67+ plasmablasts which required CD154(CD40L) signals for their propagation. Single cell RNA-sequencing revealed that THY ASCs were enriched for an interferon responsive transcriptional signature relative to those from bone marrow and spleen. Flow cytometry confirmed that THY ASCs had increased levels of Toll-like receptor 7 as well as CD69 and major histocompatibility complex class II. Overall, we identified fundamental aspects of THY ASC biology which may be leveraged for future in depth studies of this population in both health and disease.

MafB-restricted local monocyte proliferation precedes lung interstitial macrophage differentiation

Resident tissue macrophages (RTMs) are differentiated immune cells that populate distinct niches and exert important tissue-supportive functions. RTM maintenance is thought to rely either on differentiation from monocytes or on RTM self-renewal. Here, we used a mouse model of inducible lung interstitial macrophage (IM) niche depletion and refilling to investigate the development of IMs in vivo. Using time-course single-cell RNA-sequencing analyses, bone marrow chimeras and gene targeting, we found that engrafted Ly6C⁺ classical monocytes proliferated locally in a Csf1 receptor-dependent manner before differentiating into IMs. The transition from monocyte proliferation toward IM subset specification was controlled by the transcription factor MafB, while c-Maf specifically regulated the identity of the CD206⁺ IM subset. Our data provide evidence that, in the mononuclear phagocyte system, the ability to proliferate is not merely restricted to myeloid progenitor cells and mature RTMs but is also a tightly regulated capability of monocytes developing into RTMs in vivo.

Optimisation Models for Pathway Activity Inference in Cancer

BACKGROUND

With advances in high-throughput technologies, there has been an enormous increase in data related to profiling the activity of molecules in disease. While such data provide more comprehensive information on cellular actions, their large volume and complexity pose difficulty in accurate classification of disease phenotypes. Therefore, novel modelling methods that can improve accuracy while offering interpretable means of analysis are required. Biological pathways can be used to incorporate a priori knowledge of biological interactions to decrease data dimensionality and increase the biological interpretability of machine learning models.

METHODOLOGY

A mathematical optimisation model is proposed for pathway activity inference towards precise disease phenotype prediction and is applied to RNA-Seq datasets. The model is based on mixed-integer linear programming (MILP) mathematical optimisation principles and infers pathway activity as the linear combination of pathway member gene expression, multiplying expression values with model-determined gene weights that are optimised to maximise discrimination of phenotype classes and minimise incorrect sample allocation.

RESULTS

The model is evaluated on the transcriptome of breast and colorectal cancer, and exhibits solution results of good optimality as well as good prediction performance on related cancer subtypes. Two baseline pathway activity inference methods and three advanced methods are used for comparison. Sample prediction accuracy, robustness against noise expression data, and survival analysis suggest competitive prediction performance of our model while providing interpretability and insight on key pathways and genes. Overall, our work demonstrates that the flexible nature of mathematical programming lends itself well to developing efficient computational strategies for pathway activity inference and disease subtype prediction.

Single-cell transcriptomics uncovers the differentiation of a subset of murine esophageal progenitors into taste buds in vivo

Mouse esophagus is lined with a stratified epithelium, which is maintained by the constant renewal of unipotent progenitors. In this study, we profiled mouse esophagus by single-cell RNA sequencing and found taste buds specifically in the cervical segment of the esophagus. These taste buds have the same cellular composition as the ones from the tongue but express fewer taste receptor types. State-of-the-art transcriptional regulatory network analysis allowed the identification of specific transcription factors associated to the differentiation of immature progenitors into the three different taste bud cell types. Lineage tracing experiments revealed that esophageal taste buds arise from squamous bipotent progenitor, thus demonstrating that all esophageal progenitors are not unipotent. Our cell resolution characterization of cervical esophagus epithelium will enable a better understanding of esophageal progenitor potency and insights into the mechanisms involved in the development of taste buds.

Human umbilical cord mesenchymal stem cell-derived exosomes promote murine skin wound healing by neutrophil and macrophage modulations revealed by single-cell RNA sequencing

Introduction

Full-thickness skin wound healing remains a serious undertaking for patients. While stem cell-derived exosomes have been proposed as a potential therapeutic approach, the underlying mechanism of action has yet to be fully elucidated. The current study aimed to investigate the impact of exosomes derived from human umbilical cord mesenchymal stem cells (hucMSC-Exosomes) on the single-cell transcriptome of neutrophils and macrophages in the context of wound healing.

Methods

Utilizing single-cell RNA sequencing, the transcriptomic diversity of neutrophils and macrophages was analyzed in order to predict the cellular fate of these immune cells under the influence of hucMSC-Exosomes and to identify alterations of ligand-receptor interactions that may influence the wound microenvironment. The validity of the findings obtained from this analysis was subsequently corroborated by immunofluorescence, ELISA, and qRT-PCR. Neutrophil origins were characterized based on RNA velocity profiles.

Results

The expression of RETNLG and SLC2A3 was associated with migrating neutrophils, while BCL2A1B was linked to proliferating neutrophils. The hucMSC-Exosomes group exhibited significantly higher levels of M1 macrophages (215 vs 76, p < 0.00001), M2 macrophages (1231 vs 670, p < 0.00001), and neutrophils (930 vs 157, p < 0.00001) when compared to control group. Additionally, it was observed that hucMSC-Exosomes elicit alterations in the differentiation trajectories of macrophages towards more anti-inflammatory phenotypes, concomitant with changes in ligand-receptor interactions, thereby facilitating healing.

Discussion

This study has revealed the transcriptomic heterogeneity of neutrophils and macrophages in the context of skin wound repair following hucMSC-Exosomes interventions, providing a deeper understanding of cellular responses to hucMSC-Exosomes, a rising target of wound healing intervention.

Microglia drive transient insult-induced brain injury by chemotactic recruitment of CD8+ T lymphocytes

The crosstalk between the nervous and immune systems has gained increasing attention for its emerging role in neurological diseases. Radiation-induced brain injury (RIBI) remains the most common medical complication of cranial radiotherapy, and its pathological mechanisms have yet to be elucidated. Here, using single-cell RNA and T cell receptor sequencing, we found infiltration and clonal expansion of CD8⁺ T lymphocytes in the lesioned brain tissues of RIBI patients. Furthermore, by strategies of genetic or pharmacologic interruption, we identified a chemotactic action of microglia-derived CCL2/CCL8 chemokines in mediating the infiltration of CCR2⁺/CCR5⁺ CD8⁺ T cells and tissue damage in RIBI mice. Such a chemotactic axis also participated in the progression of cerebral infarction in the mouse model of ischemic injury. Our findings therefore highlight the critical role of microglia in mediating the dysregulation of adaptive immune responses and reveal a potential therapeutic strategy for non-infectious brain diseases.

Single-Cell Transcriptomics To Define Plasmodium falciparum Stage Transition in the Mosquito Midgut

Malaria inflicts the highest rate of morbidity and mortality among the vector-borne diseases. The dramatic bottleneck of parasite numbers that occurs in the gut of the obligatory mosquito vector provides a promising target for novel control strategies. Using single-cell transcriptomics, we analyzed Plasmodium falciparum development in the mosquito gut, from unfertilized female gametes through the first 20 h after blood feeding, including the zygote and ookinete stages. This study revealed the temporal gene expression of the ApiAP2 family of transcription factors and of parasite stress genes in response to the harsh environment of the mosquito midgut. Further, employing structural protein prediction analyses, we found several upregulated genes predicted to encode intrinsically disordered proteins (IDPs), a category of proteins known for their importance in regulation of transcription, translation, and protein-protein interactions. IDPs are known for their antigenic properties and may serve as suitable targets for antibody- or peptide-based transmission suppression strategies. In total, this study uncovers the P. falciparum transcriptome from early to late parasite development in the mosquito midgut, inside its natural vector, which provides an important resource for future malaria transmission-blocking initiatives. IMPORTANCE The malaria parasite Plasmodium falciparum causes more than half a million deaths per year. The current treatment regimen targets the symptom-causing blood stage inside the human host. However, recent incentives in the field call for novel interventions to block parasite transmission from humans to the mosquito vector. Therefore, we need to better understand the parasite biology during its development inside the mosquito, including a deeper understanding of the expression of genes controlling parasite progression during these stages. Here, we have generated single-cell transcriptome data, covering P. falciparum's development, from gamete to ookinete inside the mosquito midgut, uncovering previously untapped parasite biology, including a repertoire of novel biomarkers to be explored in future transmission-blocking efforts. We anticipate that our study provides an important resource, which can be further explored to improve our understanding of the parasite biology as well as aid in guiding future malaria intervention strategies.

Single-cell transcriptomic atlas of Alzheimer's disease middle temporal gyrus reveals region, cell type and sex specificity of gene expression with novel genetic risk for MERTK in female

Alzheimer's disease, the most common age-related neurodegenerative disease, is closely associated with both amyloid-ß plaque and neuroinflammation. Two thirds of Alzheimer's disease patients are females and they have a higher disease risk. Moreover, women with Alzheimer's disease have more extensive brain histological changes than men along with more severe cognitive symptoms and neurodegeneration. To identify how sex difference induces structural brain changes, we performed unbiased massively parallel single nucleus RNA sequencing on Alzheimer's disease and control brains focusing on the middle temporal gyrus, a brain region strongly affected by the disease but not previously studied with these methods. We identified a subpopulation of selectively vulnerable layer 2/3 excitatory neurons that that were RORB-negative and CDH9-expressing. This vulnerability differs from that reported for other brain regions, but there was no detectable difference between male and female patterns in middle temporal gyrus samples. Disease-associated, but sex-independent, reactive astrocyte signatures were also present. In clear contrast, the microglia signatures of diseased brains differed between males and females. Combining single cell transcriptomic data with results from genome-wide association studies (GWAS), we identified MERTK genetic variation as a risk factor for Alzheimer's disease selectively in females. Taken together, our single cell dataset revealed a unique cellular-level view of sex-specific transcriptional changes in Alzheimer's disease, illuminating GWAS identification of sex-specific Alzheimer's risk genes. These data serve as a rich resource for interrogation of the molecular and cellular basis of Alzheimer's disease.

A Novel Molecular Classification Method for Glioblastoma Based on Tumor Cell Differentiation Trajectories

The latest 2021 WHO classification redefines glioblastoma (GBM) as the hierarchical reporting standard by eliminating glioblastoma, IDH-mutant and only retaining the tumor entity of "glioblastoma, IDH-wild type." Knowing that subclassification of tumors based on molecular features is supposed to facilitate the therapeutic choice and increase the response rate in cancer patients, it is necessary to carry out molecular classification of the newly defined GBM. Although differentiation trajectory inference based on single-cell sequencing (scRNA-seq) data holds great promise for identifying cell heterogeneity, it has not been used in the study of GBM molecular classification. Single-cell transcriptome sequencing data from 10 GBM samples were used to identify molecular classification based on differentiation trajectories. The expressions of identified features were validated by public bulk RNA-sequencing data. Clinical feasibility of the classification system was examined in tissue samples by immunohistochemical (IHC) staining and immunofluorescence, and their clinical significance was investigated in public cohorts and clinical samples with complete clinical follow-up information. By analyzing scRNA-seq data of 10 GBM samples, four differentiation trajectories from the glioblastoma stem cell-like (GSCL) cluster were identified, based on which malignant cells were classified into five characteristic subclusters. Each cluster exhibited different potential drug sensitivities, pathways, functions, and transcriptional modules. The classification model was further examined in TCGA and CGGA datasets. According to the different abundance of five characteristic cell clusters, the patients were classified into five groups which we named Ac-G, Class-G, Neo-G, Opc-G, and Undiff-G groups. It was found that the Undiff-G group exhibited the worst overall survival (OS) in both TCGA and CGGA cohorts. In addition, the classification model was verified by IHC staining in 137 GBM samples to further clarify the difference in OS between the five groups. Furthermore, the novel biomarkers of glioblastoma stem cells (GSCs) were also described. In summary, we identified five classifications of GBM and found that they exhibited distinct drug sensitivities and different prognoses, suggesting that the new grouping system may be able to provide important prognostic information and have certain guiding significance for the treatment of GBM, and identified the GSCL cluster in GBM tissues and described its characteristic program, which may help develop new potential therapeutic targets for GSCs in GBM.

Pseudo-temporal dynamics of chemoresistant triple negative breast cancer cells reveal EGFR/HER2 inhibition as synthetic lethal during mid-neoadjuvant chemotherapy

In the absence of targetable hormonal axes, chemoresistance for triple-negative breast cancer (TNBC) often compromises patient outcomes. To investigate the underlying tumor dynamics, we performed trajectory analysis on the single-nuclei RNA-seq (snRNA-seq) of chemoresistant tumor clones during neoadjuvant chemotherapy (NAC). It revealed a common tumor trajectory across multiple patients with HER2-like expansions during NAC. Genome-wide CRISPR-Cas9 knock-out on mammary epithelial cells revealed chemosensitivity-promoting knock-outs were up-regulated along the tumor trajectory. Furthermore, we derived a consensus gene signature of TNBC chemoresistance by comparing the trajectory transcriptome with chemoresistant transcriptomes from TNBC cell lines and poor prognosis patient samples to predict FDA-approved drugs, including afatinib (pan-HER inhibitor), targeting the consensus signature. We validated the synergistic efficacy of afatinib and paclitaxel in chemoresistant TNBC cells and confirmed pharmacological suppression of the consensus signature. The study provides a dynamic model of chemoresistant tumor transcriptome, and computational framework for pharmacological intervention.

Screening cell-cell communication in spatial transcriptomics via collective optimal transport

Spatial transcriptomic technologies and spatially annotated single-cell RNA sequencing datasets provide unprecedented opportunities to dissect cell-cell communication (CCC). However, incorporation of the spatial information and complex biochemical processes required in the reconstruction of CCC remains a major challenge. Here, we present COMMOT (COMMunication analysis by Optimal Transport) to infer CCC in spatial transcriptomics, which accounts for the competition between different ligand and receptor species as well as spatial distances between cells. A collective optimal transport method is developed to handle complex molecular interactions and spatial constraints. Furthermore, we introduce downstream analysis tools to infer spatial signaling directionality and genes regulated by signaling using machine learning models. We apply COMMOT to simulation data and eight spatial datasets acquired with five different technologies to show its effectiveness and robustness in identifying spatial CCC in data with varying spatial resolutions and gene coverages. Finally, COMMOT identifies new CCCs during skin morphogenesis in a case study of human epidermal development.

Complex hierarchical structures in single-cell genomics data unveiled by deep hyperbolic manifold learning

With the advances in single-cell sequencing techniques, numerous analytical methods have been developed for delineating cell development. However, most are based on Euclidean space, which would distort the complex hierarchical structure of cell differentiation. Recently, methods acting on hyperbolic space have been proposed to visualize hierarchical structures in single-cell RNA-seq (scRNA-seq) data and have been proven to be superior to methods acting on Euclidean space. However, these methods have fundamental limitations and are not optimized for the highly sparse single-cell count data. To address these limitations, we propose scDHMap, a model-based deep learning approach to visualize the complex hierarchical structures of scRNA-seq data in low-dimensional hyperbolic space. The evaluations on extensive simulation and real experiments show that scDHMap outperforms existing dimensionality-reduction methods in various common analytical tasks as needed for scRNA-seq data, including revealing trajectory branches, batch correction, and denoising the count matrix with high dropout rates. In addition, we extend scDHMap to visualize single-cell ATAC-seq data.

A topographic atlas defines developmental origins of cell heterogeneity in the human embryonic lung

The lung contains numerous specialized cell types with distinct roles in tissue function and integrity. To clarify the origins and mechanisms generating cell heterogeneity, we created a comprehensive topographic atlas of early human lung development. Here we report 83 cell states and several spatially resolved developmental trajectories and predict cell interactions within defined tissue niches. We integrated single-cell RNA sequencing and spatially resolved transcriptomics into a web-based, open platform for interactive exploration. We show distinct gene expression programmes, accompanying sequential events of cell differentiation and maturation of the secretory and neuroendocrine cell types in proximal epithelium. We define the origin of airway fibroblasts associated with airway smooth muscle in bronchovascular bundles and describe a trajectory of Schwann cell progenitors to intrinsic parasympathetic neurons controlling bronchoconstriction. Our atlas provides a rich resource for further research and a reference for defining deviations from homeostatic and repair mechanisms leading to pulmonary diseases.

Epiblast-like stem cells established by Wnt/β-catenin signaling manifest distinct features of formative pluripotency and germline competence

Different formative pluripotent stem cells harboring similar functional properties have been recently established to be lineage neutral and germline competent yet have distinct molecular identities. Here, we show that WNT/β-catenin signaling activation sustains transient mouse epiblast-like cells as epiblast-like stem cells (EpiLSCs). EpiLSCs display metastable formative pluripotency with bivalent cellular energy metabolism and unique transcriptomic features and chromatin accessibility. We develop single-cell stage label transfer (scSTALT) to study the formative pluripotency continuum and reveal that EpiLSCs recapitulate a unique developmental period in vivo, filling the gap of the formative pluripotency continuum between other published formative stem cells. WNT/β-catenin signaling activation counteracts differentiation effects of activin A and bFGF by preventing complete dissolution of naive pluripotency regulatory network. Moreover, EpiLSCs have direct competence toward germline specification, which is further matured by an FGF receptor inhibitor. Our EpiLSCs can serve as an in vitro model for mimicking and studying early post-implantation development and pluripotency transition.

Lineage-specific regulatory changes in hypertrophic cardiomyopathy unraveled by single-nucleus RNA-seq and spatial transcriptomics

Hypertrophic cardiomyopathy (HCM) is the most common cardiac genetic disorder characterized by cardiomyocyte hypertrophy and cardiac fibrosis. Pathological cardiac remodeling in the myocardium of HCM patients may progress to heart failure. An in-depth elucidation of the lineage-specific changes in pathological cardiac remodeling of HCM is pivotal for the development of therapies to mitigate the progression. Here, we performed single-nucleus RNA-seq of the cardiac tissues from HCM patients or healthy donors and conducted spatial transcriptomic assays on tissue sections from patients. Unbiased clustering of 55,122 nuclei from HCM and healthy conditions revealed 9 cell lineages and 28 clusters. Lineage-specific changes in gene expression, subpopulation composition, and intercellular communication in HCM were discovered through comparative analyses. According to the results of pseudotime ordering, differential expression analysis, and differential regulatory network analysis, potential key genes during the transition towards a failing state of cardiomyocytes such as FGF12, IL31RA, and CREB5 were identified. Transcriptomic dynamics underlying cardiac fibroblast activation were also uncovered, and potential key genes involved in cardiac fibrosis were obtained such as AEBP1, RUNX1, MEOX1, LEF1, and NRXN3. Using the spatial transcriptomic data, spatial activity patterns of the candidate genes, pathways, and subpopulations were confirmed on patient tissue sections. Moreover, we showed experimental evidence that in vitro knockdown of AEBP1 could promote the activation of human cardiac fibroblasts, and overexpression of AEBP1 could attenuate the TGFβ-induced activation. Our study provided a comprehensive analysis of the lineage-specific regulatory changes in HCM, which laid the foundation for targeted drug development in HCM.

TCDD dysregulation of lncRNA expression, liver zonation and intercellular communication across the liver lobule

The persistent environmental aryl hydrocarbon receptor agonist and hepatotoxin TCDD (2,3,7,8-tetrachlorodibenzo- p -dioxin) induces hepatic lipid accumulation (steatosis), inflammation (steatohepatitis) and fibrosis. Thousands of liver-expressed, nuclear-localized lncRNAs with regulatory potential have been identified; however, their roles in TCDD-induced hepatoxicity and liver disease are unknown. We analyzed single nucleus (sn)RNA-seq data from control and chronic TCDD-exposed mouse liver to determine liver cell-type specificity, zonation and differential expression profiles for thousands of IncRNAs. TCDD dysregulated >4,000 of these lncRNAs in one or more liver cell types, including 684 lncRNAs specifically dysregulated in liver non-parenchymal cells. Trajectory inference analysis revealed major disruption by TCDD of hepatocyte zonation, affecting >800 genes, including 121 IncRNAs, with strong enrichment for lipid metabolism genes. TCDD also dysregulated expression of >200 transcription factors, including 19 Nuclear Receptors, most notably in hepatocytes and Kupffer cells. TCDD-induced changes in cellâ€"cell communication patterns included marked decreases in EGF signaling from hepatocytes to non-parenchymal cells and increases in extracellular matrix-receptor interactions central to liver fibrosis. Gene regulatory networks constructed from the snRNA-seq data identified TCDD-exposed liver network-essential lncRNA regulators linked to functions such as fatty acid metabolic process, peroxisome and xenobiotic metabolic. Networks were validated by the striking enrichments that predicted regulatory IncRNAs showed for specific biological pathways. These findings highlight the power of snRNA-seq to discover functional roles for many xenobiotic-responsive lncRNAs in both hepatocytes and liver non-parenchymal cells and to elucidate novel aspects of foreign chemical-induced hepatotoxicity and liver disease, including dysregulation of intercellular communication within the liver lobule.

Single-cell transcriptomic and spatial landscapes of the developing human pancreas

Current differentiation protocols have not been successful in reproducibly generating fully functional human beta cells in vitro, partly due to incomplete understanding of human pancreas development. Here, we present detailed transcriptomic analysis of the various cell types of the developing human pancreas, including their spatial gene patterns. We integrated single-cell RNA sequencing with spatial transcriptomics at multiple developmental time points and revealed distinct temporal-spatial gene cascades. Cell trajectory inference identified endocrine progenitor populations and branch-specific genes as the progenitors differentiate toward alpha or beta cells. Spatial differentiation trajectories indicated that Schwann cells are spatially co-located with endocrine progenitors, and cell-cell connectivity analysis predicted that they may interact via L1CAM-EPHB2 signaling. Our integrated approach enabled us to identify heterogeneity and multiple lineage dynamics within the mesenchyme, showing that it contributed to the exocrine acinar cell state. Finally, we have generated an interactive web resource for investigating human pancreas development for the research community.

Analysis of Single-Cell RNA-seq Data

As single-cell RNA sequencing experiments continue to advance scientific discoveries across biological disciplines, an increasing number of analysis tools and workflows for analyzing the data have been developed. In this chapter, we describe a standard workflow and elaborate on relevant data analysis tools for analyzing single-cell RNA sequencing data. We provide recommendations for the appropriate use of commonly used methods, with code examples and analysis interpretations.

TrackSOM: Mapping immune response dynamics through clustering of time-course cytometry data

Mapping the dynamics of immune cell populations over time or disease-course is key to understanding immunopathogenesis and devising putative interventions. We present TrackSOM, a novel method for delineating cellular populations and tracking their development over a time- or disease-course cytometry datasets. We demonstrate TrackSOM-enabled elucidation of the immune response to West Nile Virus infection in mice, uncovering heterogeneous subpopulations of immune cells and relating their functional evolution to disease severity. TrackSOM is easy to use, encompasses few parameters, is quick to execute, and enables an integrative and dynamic overview of the immune system kinetics that underlie disease progression and/or resolution.

Characterization of diverse populations of sinoatrial node cells and their proliferation potential at single nucleus resolution

Background

Each heartbeat is initiated in the sinoatrial node (SAN), and although a recent study (GSE130710) using single nucleus RNA-seq had discovered different populations of cell types within SAN tissue, the distinct potential functions of these cell types have not been delineated.

Methods

To infer some special potential functions of different SAN cell clusters, we applied principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP) to the GSE130710 dataset to reduce dimensions, followed by Pseudotime trajectory and AUCell analyses, ANOVA and Hurdle statistical models, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichments to determine functional potential of cell types. Nuclear EdU immuno-labeling of SAN tissue confirmed cell type proliferation.

Findings

We identified elements of a coupled clock system known to drive SAN cell pacemaking within the GSE130710 sinus node myocyte cluster, which, surprisingly, manifested signals of suppressed fatty acid and nitrogen metabolism and reduced immune gene expression. Proliferation signaling was enriched in endocardial, epicardial, epithelial cells, and macrophages, in which, fatty acid and nitrogen metabolic signals were also suppressed, but immune signaling was enhanced. EdU labeling was rare in pacemaker cells but was robust in interstitial cells.

Interpretation

Pacemaker cells that initiate each heartbeat manifest suppressed fatty acid and nitrogen metabolism and limited immune signaling and proliferation potential. In contrast, other populations of SAN cells not directly involved in the initiation of heartbeats, manifest robust proliferation and immune potential, likely to ensure an environment required to sustain healthy SAN tissue pacemaker function.

Transplanting rejuvenated blood stem cells extends lifespan of aged immunocompromised mice

One goal of regenerative medicine is to rejuvenate tissues and extend lifespan by restoring the function of endogenous aged stem cells. However, evidence that somatic stem cells can be targeted in vivo to extend lifespan is still lacking. Here, we demonstrate that after a short systemic treatment with a specific inhibitor of the small RhoGTPase Cdc42 (CASIN), transplanting aged hematopoietic stem cells (HSCs) from treated mice is sufficient to extend the healthspan and lifespan of aged immunocompromised mice without additional treatment. In detail, we show that systemic CASIN treatment improves strength and endurance of aged mice by increasing the myogenic regenerative potential of aged skeletal muscle stem cells. Further, we show that CASIN modifies niche localization and H4K16ac polarity of HSCs in vivo. Single-cell profiling reveals changes in HSC transcriptome, which underlie enhanced lymphoid and regenerative capacity in serial transplantation assays. Overall, we provide proof-of-concept evidence that a short systemic treatment to decrease Cdc42 activity improves the regenerative capacity of different endogenous aged stem cells in vivo, and that rejuvenated HSCs exert a broad systemic effect sufficient to extend murine health- and lifespan.

From pseudo to real-time dynamics of T cell thymic differentiation

Numerous methods have recently emerged for ordering single cells along developmental trajectories. However, accurate depiction of developmental dynamics can only be achieved after rescaling the trajectory according to the relative time spent at each developmental point. We formulate a model which estimates local cell densities and fluxes, and incorporates cell division and apoptosis rates, to infer the real-time dimension of the developmental trajectory. We validate the model using mathematical simulations and apply it to experimental high dimensional cytometry data obtained from the mouse thymus to construct the true time profile of the thymocyte developmental process. Our method can easily be implemented in any of the existing tools for trajectory inference.

Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell immunoprofiling

Introduction

SARS-CoV-2 infection results in varying disease severity, ranging from asymptomatic infection to severe illness. A detailed understanding of the immune response to SARS-CoV-2 is critical to unravel the causative factors underlying differences in disease severity and to develop optimal vaccines against new SARS-CoV-2 variants.

Methods

We combined single-cell RNA and T cell receptor sequencing with CITE-seq antibodies to characterize the CD8⁺ T cell response to SARS-CoV-2 infection at high resolution and compared responses between mild and severe COVID-19.

Results

We observed increased CD8⁺ T cell exhaustion in severe SARS-CoV-2 infection and identified a population of NK-like, terminally differentiated CD8⁺ effector T cells characterized by expression of FCGR3A (encoding CD16). Further characterization of NK-like CD8⁺ T cells revealed heterogeneity among CD16⁺ NK-like CD8⁺ T cells and profound differences in cytotoxicity, exhaustion, and NK-like differentiation between mild and severe disease conditions.

Discussion

We propose a model in which differences in the surrounding inflammatory milieu lead to crucial differences in NK-like differentiation of CD8⁺ effector T cells, ultimately resulting in the appearance of NK-like CD8⁺ T cell populations of different functionality and pathogenicity. Our in-depth characterization of the CD8⁺ T cell-mediated response to SARS-CoV-2 infection provides a basis for further investigation of the importance of NK-like CD8⁺ T cells in COVID-19 severity.