Single-cell transcriptional diversity is a hallmark of developmental potential

Mammary cell gene expression atlas links epithelial cell remodeling events to breast carcinogenesis

The female mammary epithelium undergoes reorganization during development, pregnancy, and menopause, linking higher risk with breast cancer development. To characterize these periods of complex remodeling, here we report integrated 50 K mouse and 24 K human mammary epithelial cell atlases obtained by single-cell RNA sequencing, which covers most lifetime stages. Our results indicate a putative trajectory that originates from embryonic mammary stem cells which differentiates into three epithelial lineages (basal, luminal hormone-sensing, and luminal alveolar), presumably arising from unipotent progenitors in postnatal glands. The lineage-specific genes infer cells of origin of breast cancer using The Cancer Genome Atlas data and single-cell RNA sequencing of human breast cancer, as well as the association of gland reorganization to different breast cancer subtypes. This comprehensive mammary cell gene expression atlas ( https://mouse-mammary-epithelium-integrated.cells.ucsc.edu ) presents insights into the impact of the internal and external stimuli on the mammary epithelium at an advanced resolution.

Single-Cell Sequencing Methodologies: From Transcriptome to Multi-Dimensional Measurement

Cells are the basic building blocks of biological systems, with inherent unique molecular features and development trajectories. The study of single cells facilitates in-depth understanding of cellular diversity, disease processes, and organization of multicellular organisms. Single-cell RNA sequencing (scRNA-seq) technologies have become essential tools for the interrogation of gene expression patterns and the dynamics of single cells, allowing cellular heterogeneity to be dissected at unprecedented resolution. Nevertheless, measuring at only transcriptome level or 1D is incomplete; the cellular heterogeneity reflects in multiple dimensions, including the genome, epigenome, transcriptome, spatial, and even temporal dimensions. Hence, integrative single cell analysis is highly desired. In addition, the way to interpret sequencing data by virtue of bioinformatic tools also exerts critical roles in revealing differential gene expression. Here, a comprehensive review that summarizes the cutting-edge single-cell transcriptome sequencing methodologies, including scRNA-seq, spatial and temporal transcriptome profiling, multi-omics sequencing and computational methods developed for scRNA-seq data analysis is provided. Finally, the challenges and perspectives of this field are discussed.

Current progress and potential opportunities to infer single-cell developmental trajectory and cell fate

Rapid technological advances in transcriptomics and lineage tracing technologies provide new opportunities to understand organismal development at the single-cell level. Building on these advances, various computational methods have been proposed to infer developmental trajectories and to predict cell fate. These methods have unveiled previously uncharacterized transitional cell types and differentiation processes. Importantly, the ability to recover cell states and trajectories has been evolving hand-in-hand with new technologies and diverse experimental designs; more recent methods can capture complex trajectory topologies and infer short- and long-term cell fate dynamics. Here, we summarize and categorize the most recent and popular computational approaches for trajectory inference based on the information they leverage and describe future challenges and opportunities for the development of new methods for reconstructing differentiation trajectories and inferring cell fates.

Single-cell transcriptomic analyses provide insights into the developmental origins of neuroblastoma

Neuroblastoma is a pediatric tumor of the developing sympathetic nervous system. However, the cellular origin of neuroblastoma has yet to be defined. Here we studied the single-cell transcriptomes of neuroblastomas and normal human developing adrenal glands at various stages of embryonic and fetal development. We defined normal differentiation trajectories from Schwann cell precursors over intermediate states to neuroblasts or chromaffin cells and showed that neuroblastomas transcriptionally resemble normal fetal adrenal neuroblasts. Importantly, neuroblastomas with varying clinical phenotypes matched different temporal states along normal neuroblast differentiation trajectories, with the degree of differentiation corresponding to clinical prognosis. Our work highlights the roles of oncogenic MYCN and loss of TFAP2B in blocking differentiation and may provide the basis for designing therapeutic interventions to overcome differentiation blocks.

Mammary epithelial cells have lineage-rooted metabolic identities

Cancer metabolism adapts the metabolic network of its tissue of origin. However, breast cancer is not a disease of a single origin. Multiple epithelial populations serve as the culprit cell of origin for specific breast cancer subtypes, yet our knowledge of the metabolic network of normal mammary epithelial cells is limited. Using a multi-omic approach, here we identify the diverse metabolic programmes operating in normal mammary populations. The proteomes of basal, luminal progenitor and mature luminal cell populations revealed enrichment of glycolysis in basal cells and of oxidative phosphorylation in luminal progenitors. Single-cell transcriptomes corroborated lineage-specific metabolic identities and additional intra-lineage heterogeneity. Mitochondrial form and function differed across lineages, with clonogenicity correlating with mitochondrial activity. Targeting oxidative phosphorylation and glycolysis with inhibitors exposed lineage-rooted metabolic vulnerabilities of mammary progenitors. Bioinformatics indicated breast cancer subtypes retain metabolic features of their putative cell of origin. Thus, lineage-rooted metabolic identities of normal mammary cells may underlie breast cancer metabolic heterogeneity and targeting these vulnerabilities could advance breast cancer therapy.

Single-cell sequencing of human white adipose tissue identifies new cell states in health and obesity

White adipose tissue (WAT) is an essential regulator of energy storage and systemic metabolic homeostasis. Regulatory networks consisting of immune and structural cells are necessary to maintain WAT metabolism, which can become impaired during obesity in mammals. Using single-cell transcriptomics and flow cytometry, we unveil a large-scale comprehensive cellular census of the stromal vascular fraction of healthy lean and obese human WAT. We report new subsets and developmental trajectories of adipose-resident innate lymphoid cells, dendritic cells and monocyte-derived macrophage populations that accumulate in obese WAT. Analysis of cell-cell ligand-receptor interactions and obesity-enriched signaling pathways revealed a switch from immunoregulatory mechanisms in lean WAT to inflammatory networks in obese WAT. These results provide a detailed and unbiased cellular landscape of homeostatic and inflammatory circuits in healthy human WAT.

Single-cell RNA-seq reveals transcriptional landscape and intratumor heterogenicity in gallbladder cancer liver metastasis microenvironment

BACKGROUND

Gallbladder cancer (GBC) is a highly aggressive biliary epithelial malignancy. The median survival time of GBC patients was less than 1 year. Tumor invasion and metastasis are the major cause of high mortality of GBC patients. However, the molecular mechanisms involved in GBC metastases are still unclear.

METHODS

We performed 10X genomics single-cell RNA sequencing (scRNA-seq) on GBC liver metastasis tissue to evaluate the characteristics of the GBC liver metastasis microenvironment.

RESULTS

In this study, 8 cell types, a total of 7,788 cells, including T cells, B cells, malignant cells, fibroblasts, endothelial cells, macrophages, dendritic cells (DCs), and mast cells were identified. Malignant cells displayed a high degree of intratumor heterogenicity, while neutrophils were found to promote GBC cell proliferation, migration, and invasion. Furthermore, cytotoxic cluster of differentiation (CD8+) T cells became exhausted and CD4+ regulatory T cells (Tregs) exhibited immunosuppressive characteristics. Macrophages played an important role in the tumor microenvironment (TME). We identified three distinct macrophage subsets and emergent M2 polarization. We also found that cancer-associated fibroblasts exhibited heterogeneity and may be associated with GBC metastasis.

CONCLUSIONS

Although preliminary in nature, our study provides a landscape view at the single-cell level. These results offer a unique perspective into understanding the liver metastasis of GBC.

Cascade diversification directs generation of neuronal diversity in the hypothalamus

The hypothalamus contains an astounding heterogeneity of neurons that regulate endocrine, autonomic, and behavioral functions. However, its molecular developmental trajectory and origin of neuronal diversity remain unclear. Here, we profile the transcriptome of 43,261 cells derived from Rax⁺ hypothalamic neuroepithelium to map the developmental landscape of the mouse hypothalamus and trajectory of radial glial cells (RGCs), intermediate progenitor cells (IPCs), nascent neurons, and peptidergic neurons. We show that RGCs adopt a conserved strategy for multipotential differentiation but generate Ascl1⁺ and Neurog2⁺ IPCs. Ascl1⁺ IPCs differ from their telencephalic counterpart by displaying fate bifurcation, and postmitotic nascent neurons resolve into multiple peptidergic neuronal subtypes. Clonal analysis further demonstrates that single RGCs can produce multiple neuronal subtypes. Our study reveals that multiple cell types along the lineage hierarchy contribute to fate diversification of hypothalamic neurons in a stepwise fashion, suggesting a cascade diversification model that deconstructs the origin of neuronal diversity.

MyoD induces ARTD1 and nucleoplasmic poly-ADP-ribosylation during fibroblast to myoblast transdifferentiation

While protein ADP-ribosylation was reported to regulate differentiation and dedifferentiation, it has so far not been studied during transdifferentiation. Here, we found that MyoD-induced transdifferentiation of fibroblasts to myoblasts promotes the expression of the ADP-ribosyltransferase ARTD1. Comprehensive analysis of the genome architecture by Hi-C and RNA-seq analysis during transdifferentiation indicated that ARTD1 locally contributed to A/B compartmentalization and coregulated a subset of MyoD target genes that were however not sufficient to alter transdifferentiation. Surprisingly, the expression of ARTD1 was accompanied by the continuous synthesis of nuclear ADP ribosylation that was neither dependent on the cell cycle nor induced by DNA damage. Conversely to the H₂O₂-induced ADP-ribosylation, the MyoD-dependent ADP-ribosylation was not associated to chromatin but rather localized to the nucleoplasm. Together, these data describe a MyoD-induced nucleoplasmic ADP-ribosylation that is observed particularly during transdifferentiation and thus potentially expands the plethora of cellular processes associated with ADP-ribosylation.

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MyoD-dependent transdifferentiation of IMR90 to myoblasts induces ARTD1 expression

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Transdifferentiation induces nuclear ARTD1-dependent ADP-ribosylation in myoblasts

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This ADP-ribosylation is induced independent of cell cycle and of DNA damage

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ARTD1-mediated poly-ADP-ribosylation localizes to the nucleoplasm in myoblasts

Mouse aging cell atlas analysis reveals global and cell type-specific aging signatures

Aging is associated with complex molecular and cellular processes that are poorly understood. Here we leveraged the Tabula Muris Senis single-cell RNA-seq data set to systematically characterize gene expression changes during aging across diverse cell types in the mouse. We identified aging-dependent genes in 76 tissue-cell types from 23 tissues and characterized both shared and tissue-cell-specific aging behaviors. We found that the aging-related genes shared by multiple tissue-cell types also change their expression congruently in the same direction during aging in most tissue-cell types, suggesting a coordinated global aging behavior at the organismal level. Scoring cells based on these shared aging genes allowed us to contrast the aging status of different tissues and cell types from a transcriptomic perspective. In addition, we identified genes that exhibit age-related expression changes specific to each functional category of tissue-cell types. Altogether, our analyses provide one of the most comprehensive and systematic characterizations of the molecular signatures of aging across diverse tissue-cell types in a mammalian system.

Single-cell resolution of lineage trajectories in the Arabidopsis stomatal lineage and developing leaf

Dynamic cell identities underlie flexible developmental programs. The stomatal lineage in the Arabidopsis leaf epidermis features asynchronous and indeterminate divisions that can be modulated by environmental cues. The products of the lineage, stomatal guard cells and pavement cells, regulate plant-atmosphere exchanges, and the epidermis as a whole influences overall leaf growth. How flexibility is encoded in development of the stomatal lineage and how cell fates are coordinated in the leaf are open questions. Here, by leveraging single-cell transcriptomics and molecular genetics, we uncovered models of cell differentiation within Arabidopsis leaf tissue. Profiles across leaf tissues identified points of regulatory congruence. In the stomatal lineage, single-cell resolution resolved underlying cell heterogeneity within early stages and provided a fine-grained profile of guard cell differentiation. Through integration of genome-scale datasets and spatiotemporally precise functional manipulations, we also identified an extended role for the transcriptional regulator SPEECHLESS in reinforcing cell fate commitment.

Novel Lineage-Tracing System to Identify Site-Specific Ectopic Bone Precursor Cells

Heterotopic ossification (HO) is a form of pathological cell-fate change of mesenchymal stem/precursor cells (MSCs) that occurs following traumatic injury, limiting range of motion in extremities and causing pain. MSCs have been shown to differentiate to form bone; however, their lineage and aberrant processes after trauma are not well understood. Utilizing a well-established mouse HO model and inducible lineage-tracing mouse (Hoxa11-CreER^T2;ROSA26-LSL-TdTomato), we found that Hoxa11-lineage cells represent HO progenitors specifically in the zeugopod. Bioinformatic single-cell transcriptomic and epigenomic analyses showed Hoxa11-lineage cells are regionally restricted mesenchymal cells that, after injury, gain the potential to undergo differentiation toward chondrocytes, osteoblasts, and adipocytes. This study identifies Hoxa11-lineage cells as zeugopod-specific ectopic bone progenitors and elucidates the fate specification and multipotency that mesenchymal cells acquire after injury. Furthermore, this highlights homeobox patterning genes as useful tools to trace region-specific progenitors and enable location-specific gene deletion.

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Lineage tracing, single-cell RNA-seq and single cell ATAC enable cell specific analysis of in vivo cell fate

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Hoxa11 lineage marks distinct mesenchymal precursors in the zeugopod

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Hoxa11 lineage mesenchymal precursors undergo an aberrant cell fate change towards ectopic bone and cartilage

A pan-cancer single-cell transcriptional atlas of tumor infiltrating myeloid cells

Tumor-infiltrating myeloid cells (TIMs) are key regulators in tumor progression, but the similarity and distinction of their fundamental properties across different tumors remain elusive. Here, by performing a pan-cancer analysis of single myeloid cells from 210 patients across 15 human cancer types, we identified distinct features of TIMs across cancer types. Mast cells in nasopharyngeal cancer were found to be associated with better prognosis and exhibited an anti-tumor phenotype with a high ratio of TNF+/VEGFA+ cells. Systematic comparison between cDC1- and cDC2-derived LAMP3+ cDCs revealed their differences in transcription factors and external stimulus. Additionally, pro-angiogenic tumor-associated macrophages (TAMs) were characterized with diverse markers across different cancer types, and the composition of TIMs appeared to be associated with certain features of somatic mutations and gene expressions. Our results provide a systematic view of the highly heterogeneous TIMs and suggest future avenues for rational, targeted immunotherapies.

Reconciling Non-Genetic Plasticity with Somatic Evolution in Cancer

Post-treatment progression of tumors is commonly explained by somatic Darwinian evolution (i.e., selection of cells carrying genetic mutations that create more aggressive cell traits). But cancer genome and transcriptome analyses now paint a picture far more complex, prompting us to see beyond the Darwinian scheme: non-genetic cell phenotype plasticity explained by alternative stable gene expression states ('attractors'), may also produce aggressive phenotypes that can be selected for, without mutations. Worse, treatment may even induce cell state transitions into more malignant attractors. We review recent evidence for non-genetic mechanisms of progression, explain the theoretical foundation of attractor transitions behind treatment-induced increase of aggressiveness, and provide a framework for unifying genetic and non-genetic dynamics in tumor progression.

Organization of the Pluripotent Genome

In the past several decades, the establishment of in vitro models of pluripotency has ushered in a golden era for developmental and stem cell biology. Research in this arena has led to profound insights into the regulatory features that shape early embryonic development. Nevertheless, an integrative theory of the epigenetic principles that govern the pluripotent nucleus remains elusive. Here, we summarize the epigenetic characteristics that define the pluripotent state. We cover what is currently known about the epigenome of pluripotent stem cells and reflect on the use of embryonic stem cells as an experimental system. In addition, we highlight insights from super-resolution microscopy, which have advanced our understanding of the form and function of chromatin, particularly its role in establishing the characteristically "open chromatin" of pluripotent nuclei. Further, we discuss the rapid improvements in 3C-based methods, which have given us a means to investigate the 3D spatial organization of the pluripotent genome. This has aided the adaptation of prior notions of a "pluripotent molecular circuitry" into a more holistic model, where hotspots of co-interacting domains correspond with the accumulation of pluripotency-associated factors. Finally, we relate these earlier hypotheses to an emerging model of phase separation, which posits that a biophysical mechanism may presuppose the formation of a pluripotent-state-defining transcriptional program.

Androgen action in cell fate and communication during prostate development at single-cell resolution

Androgens/androgen receptor (AR)-mediated signaling pathways are essential for prostate development, morphogenesis and regeneration. Specifically, stromal AR signaling has been shown to be essential for prostatic initiation. However, the molecular mechanisms underlying AR-initiated mesenchymal-epithelial interactions in prostate development remain unclear. Here, using a newly generated mouse model, we have directly addressed the fate and role of genetically marked AR-expressing cells during embryonic prostate development. Androgen signaling-initiated signaling pathways were identified in mesenchymal niche populations at single-cell transcriptomic resolution. The dynamic cell-signaling networks regulated by stromal AR were additionally characterized in relation to prostatic epithelial bud formation. Pseudotime analyses further revealed the differentiation trajectory and fate of AR-expressing cells in both prostatic mesenchymal and epithelial cell populations. Specifically, the cellular properties of Zeb1-expressing progenitors were assessed. Selective deletion of AR signaling in a subpopulation of mesenchymal rather than epithelial cells dysregulated the expression of the master regulators and significantly impaired prostatic bud formation. These data provide novel, high-resolution evidence demonstrating the important role of mesenchymal androgen signaling in the cellular niche controlling prostate early development by initiating dynamic mesenchyme-epithelia cell interactions.

Zeb1 Promotes Odontoblast Differentiation in a Stage-Dependent Manner

A comprehensive study of odontoblastic differentiation is essential to understand the process of tooth development and to achieve the ability of tooth regeneration in the future. Zinc finger E-box-binding homeobox 1 (Zeb1) is a transcription factor expressed in various neural crest-derived tissues, including the mesenchyme of the tooth germ. However, its role in odontoblastic differentiation remains unknown. In this study, we found the expression of Zeb1 gradually increased during odontoblast differentiation in vivo, as well as during induced differentiation of cultured primary murine dental papilla cells (mDPCs) in vitro. In addition, the differentiation of mDPCs was repressed in Zeb1-silenced cells. We used RNA sequencing (RNA-seq) to identify the transcriptome-wide targets of Zeb1 and used assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) to explore the direct targets of Zeb1 in both the early stage (embryonic day 16.5; E16.5) and the late stage (postnatal day 0; PN0) of tooth development. We identified the motifs of transcription factors enriched in Zeb1-dependent accessible chromatin regions and observed that only in the early stage of mDPCs could Zeb1 significantly change the accessibility of chromatin regions. In vivo and in vitro experiments confirmed that silencing of Zeb1 at E16.5 inhibited dentinogenesis. Analysis of RNA-seq and ATAC-seq resulted in the identification of Runx2, a gene directly regulated by Zeb1 during early odontoblast differentiation. Zeb1 enhances the expression of Runx2 by binding to its cis-elements, and ZEB1 interacts with RUNX2. In the late stage of tooth development, we found that ZEB1 could directly bind to and increase the enhancer activity of an element upstream of Dspp and promote dentinogenesis. In this study, for the first time, we revealed that ZEB1 promoted odontoblast differentiation in the early stage by altering chromatin accessibility of cis-elements near genes such as Runx2, while in the late stage, it directly enhanced Dspp transcription, thereby performing a dual role.

Computational Stem Cell Biology: Open Questions and Guiding Principles

Computational biology is enabling an explosive growth in our understanding of stem cells and our ability to use them for disease modeling, regenerative medicine, and drug discovery. We discuss four topics that exemplify applications of computation to stem cell biology: cell typing, lineage tracing, trajectory inference, and regulatory networks. We use these examples to articulate principles that have guided computational biology broadly and call for renewed attention to these principles as computation becomes increasingly important in stem cell biology. We also discuss important challenges for this field with the hope that it will inspire more to join this exciting area.

Single-Cell Transcriptome Analysis in Plants: Advances and Challenges

The rapid and enthusiastic adoption of single-cell RNA sequencing (scRNA-seq) has demonstrated that this technology is far more than just another way to perform transcriptome analysis. It is not an exaggeration to say that the advent of scRNA-seq is revolutionizing the details of whole-transcriptome snapshots from a tissue to a cell. With this disruptive technology, it is now possible to mine heterogeneity between tissue types and within cells like never before. This enables more rapid identification of rare and novel cell types, simultaneous characterization of multiple different cell types and states, more accurate and integrated understanding of their roles in life processes, and more. However, we are only at the beginning of unlocking the full potential of scRNA-seq applications. This is particularly true for plant sciences, where single-cell transcriptome profiling is in its early stage and has many exciting challenges to overcome. In this review, we compare and evaluate recent pioneering studies using the Arabidopsis root model, which has established new paradigms for scRNA-seq studies in plants. We also explore several new and promising single-cell analysis tools that are available to those wishing to study plant development and physiology at unprecedented resolution and scale. In addition, we propose some future directions on the use of scRNA-seq technology to tackle some of the critical challenges in plant research and breeding.

Defining human mesenchymal and epithelial heterogeneity in response to oral inflammatory disease

Human oral soft tissues provide the first barrier of defence against chronic inflammatory disease and hold a remarkable scarless wounding phenotype. Tissue homeostasis requires coordinated actions of epithelial, mesenchymal, and immune cells. However, the extent of heterogeneity within the human oral mucosa and how tissue cell types are affected during the course of disease progression is unknown. Using single-cell transcriptome profiling we reveal a striking remodelling of the epithelial and mesenchymal niches with a decrease in functional populations that are linked to the aetiology of the disease. Analysis of ligand–receptor interaction pairs identify potential intercellular hubs driving the inflammatory component of the disease. Our work establishes a reference map of the human oral mucosa in health and disease, and a framework for the development of new therapeutic strategies.

Stem cell contributions to cementoblast differentiation in healthy periodontal ligament and periodontitis

Loss of tissue attachment as a consequence of bacterial infection and inflammation represents the main therapeutic target for the treatment of periodontitis. Cementoblasts, the cells that produce the mineralized tissue, cementum, that is responsible for connecting the soft periodontal tissue to the tooth, are a key cell type for maintaining/restoring tissue attachment following disease. Here, we identify two distinct stem cell populations that contribute to cementoblast differentiation at different times. During postnatal development, cementoblasts are formed from perivascular-derived cells expressing CD90 and perivascular-associated cells that express Axin2. During adult homeostasis, only Wnt-responsive Axin2+ cells form cementoblasts but following experimental induction of periodontal disease, CD90+ cells become the main source of cementoblasts. We thus show that different populations of resident stem cells are mobilized at different times and during disease to generate precursors for cementoblast differentiation and thus provide an insight into the targeting cells resident cells for novel therapeutic approaches. The differentiation of these stem cells into cementoblasts is however inhibited by bacterial products such as lipopolysaccharides, emphasizing that regeneration of periodontal ligament soft tissue and restoration of attachment will require a multipronged approach.

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.

Breast Cancer Stem Cells: Biomarkers, Identification and Isolation Methods, Regulating Mechanisms, Cellular Origin, and Beyond

Despite recent advances in diagnosis and treatment, breast cancer (BC) is still a major cause of cancer-related mortality in women. Breast cancer stem cells (BCSCs) are a small but significant subpopulation of heterogeneous breast cancer cells demonstrating strong self-renewal and proliferation properties. Accumulating evidence has proved that BCSCs are the driving force behind BC tumor initiation, progression, metastasis, drug resistance, and recurrence. As a heterogeneous disease, BC contains a full spectrum of different BC subtypes, and different subtypes of BC further exhibit distinct subtypes and proportions of BCSCs, which correspond to different treatment responses and disease-specific outcomes. This review summarized the current knowledge of BCSC biomarkers and their clinical relevance, the methods for the identification and isolation of BCSCs, and the mechanisms regulating BCSCs. We also discussed the cellular origin of BCSCs and the current advances in single-cell lineage tracing and transcriptomics and their potential in identifying the origin and lineage development of BCSCs.

Prrx1 Fibroblasts Represent a Pro-fibrotic Lineage in the Mouse Ventral Dermis

Fibroblast heterogeneity has been shown within the unwounded mouse dorsal dermis, with fibroblast subpopulations being identified according to anatomical location and embryonic lineage. Using lineage tracing, we demonstrate that paired related homeobox 1 (Prrx1)-expressing fibroblasts are responsible for acute and chronic fibroses in the ventral dermis. Single-cell transcriptomics further corroborated the inherent fibrotic characteristics of Prrx1 fibroblasts during wound repair. In summary, we identify and characterize a fibroblast subpopulation in the mouse ventral dermis with intrinsic scar-forming potential.

Uncovering cellular networks in branching morphogenesis using single-cell transcriptomics

Single-cell RNA-sequencing (scRNA-seq) and related technologies to identify cell types and measure gene expression in space, in time, and within lineages have multiplied rapidly in recent years. As these techniques proliferate, we are seeing an increase in their application to the study of developing tissues. Here, we focus on single-cell investigations of branching morphogenesis. Branched organs are highly complex but typically develop recursively, such that a given developmental stage theoretically contains the entire spectrum of cell identities from progenitor to terminally differentiated. Therefore, branched organs are a highly attractive system for study by scRNA-seq. First, we provide an update on advances in the field of scRNA-seq analysis, focusing on spatial transcriptomics, computational reconstruction of differentiation trajectories, and integration of scRNA-seq with lineage tracing. In addition, we discuss the possibilities and limitations for applying these techniques to studying branched organs. We then discuss exciting advances made using scRNA-seq in the study of branching morphogenesis and differentiation in mammalian organs, with emphasis on the lung, kidney, and mammary gland. We propose ways that scRNA-seq could be used to address outstanding questions in each organ. Finally, we highlight the importance of physical and mechanical signals in branching morphogenesis and speculate about how scRNA-seq and related techniques could be applied to study tissue morphogenesis beyond just differentiation.

Colon Cancer Heterogeneity: Welcome to the RiboZone

In this issue of Cell Stem Cell, Morral et al. (2020) shed new light on the hierarchical organization of cells within colorectal cancer. They show that tumor cells at the apex of this hierarchy reside in particular tumor zones and possess high protein synthesis activity. Interference with their biosynthetic activity results in an irreversible growth arrest of CRC.

Isobaric Tags for Relative and Absolute Quantitation in Proteomic Analysis of Potential Biomarkers in Invasive Cancer, Ductal Carcinoma In Situ, and Mammary Fibroadenoma

OBJECTIVES

Breast malignancy is a serious threat to women's health around the world. Following the rapid progress in the field of cancer diagnostics and identification of pathological markers, breast tumor treatment methods have been greatly improved. However, for invasive, ductal carcinomas and mammary fibroadenoma, there is an urgent demand for better breast tumor-linked biomarkers. The current study was designed to identify diagnostic and/or therapeutic protein biomarkers for breast tumors.

METHODS

A total of 140 individuals were included, comprising 35 healthy women, 35 invasive breast cancers (IBC), 35 breast ductal carcinomas in situ (DCIS), and 35 breast fibroadenoma patients. Isobaric tags for relative and absolute quantitation (iTRAQ) proteomic analysis was employed to characterize differentially expressed proteins for potential biomarkers in IBC, DCIS, and fibroadenomas by comparisons with their matched adjacent tissues and/or normal breast tissues. The public databases Metascape and String were used for bioinformatic analyses.

RESULTS

Using the proteomics approach, we identified differentially expressed proteins in tissues of different breast tumors compared to normal/adjacent breast tissues, including 100 in IBC, 52 in DCIS, and 44 in fibroadenoma. Among the 100 IBC differentially expressed proteins, 37 were found to be specific to this type of cancer only. Additionally, four proteins were specifically expressed in DCIS and four in fibroadenoma. Compared to corresponding adjacent tissues and normal breast tissues, 18 step-changing proteins were differentially expressed in IBC, 14 in DCIS, and 13 in fibroadenoma, respectively. Compared to DCIS and normal breast tissues, 65 proteins were differentially expressed in IBC with growing levels of malignancy.

CONCLUSIONS

The identified potential protein biomarkers may be used as diagnostic and/or therapeutic targets in breast tumors.

Cell populations in neonatal rat peripheral nerves identified by single-cell transcriptomics

Peripheral nerves connect central nerves with target tissues and organs and execute vital signal transduction functions. Although sub-types of neurons have been defined, the heterogeneity of cell populations in peripheral nerves, especially Schwann cells, has not been well demonstrated. Here, we collected sciatic nerves (SN) and dorsal root ganglia (DRG) from neonatal (1-day old) rats and classified cell populations by high-coverage single-cell sequencing. A total of 10 types of cells, including endothelial cells, erythrocytes, fibroblasts, monocytic cells, neurons, neutrophils, pericytes, satellite cells, Schwann cells, and vascular smooth muscle cells, were identified by transcriptome-based cell typing. The comparisons of cells in neonatal rat SN and DRG revealed distinct atlas in different tissue localizations. Investigations of ligand-receptor interactions showed that there existed direct cell-cell communications between endothelial cells and fibroblasts in SN and among endothelial cells, fibroblasts, and vascular smooth muscle cells in DRG. Schwann cells in neonatal rats were further sub-grouped to four sub-types, including LOC100134871 and Hbb expressing Schwann cell sub-type 1, Cldn19 and Emid1 expressing Schwann cell sub-type 2, Timp3 and Col5a3 expressing Schwann cell sub-type 3, and Cenpf and Mki67 expressing Schwann cell sub-type 4. These Schwann cell sub-types exhibited distinct genetic features and functional enrichments. Collectively, our results illustrated the diversity and cellular complexity of peripheral nerves at the neonatal stage and revealed the heterogeneity of Schwann cells in the peripheral nervous system.

Unraveling Hematopoiesis through the Lens of Genomics

Hematopoiesis has long served as a paradigm of stem cell biology and tissue homeostasis. In the past decade, the genomics revolution has ushered in powerful new methods for investigating the hematopoietic system that have provided transformative insights into its biology. As part of the advances in genomics, increasingly accurate deep sequencing and novel methods of cell tracking have revealed hematopoiesis to be more of a continuous and less of a discrete and punctuated process than originally envisioned. In part, this continuous nature of hematopoiesis is made possible by the emergent outcomes of vast, interconnected regulatory networks that influence cell fates and lineage commitment. It is also becoming clear how these mechanisms are modulated by genetic variation present throughout the population. This review describes how these recently uncovered complexities are reshaping our concept of tissue development and homeostasis while opening up a more comprehensive future understanding of hematopoiesis.

Reprogramming roadmap reveals route to human induced trophoblast stem cells

The reprogramming of human somatic cells to primed or naive induced pluripotent stem cells recapitulates the stages of early embryonic development^1-6. The molecular mechanism that underpins these reprogramming processes remains largely unexplored, which impedes our understanding and limits rational improvements to reprogramming protocols. Here, to address these issues, we reconstruct molecular reprogramming trajectories of human dermal fibroblasts using single-cell transcriptomics. This revealed that reprogramming into primed and naive pluripotency follows diverging and distinct trajectories. Moreover, genome-wide analyses of accessible chromatin showed key changes in the regulatory elements of core pluripotency genes, and orchestrated global changes in chromatin accessibility over time. Integrated analysis of these datasets revealed a role for transcription factors associated with the trophectoderm lineage, and the existence of a subpopulation of cells that enter a trophectoderm-like state during reprogramming. Furthermore, this trophectoderm-like state could be captured, which enabled the derivation of induced trophoblast stem cells. Induced trophoblast stem cells are molecularly and functionally similar to trophoblast stem cells derived from human blastocysts or first-trimester placentas⁷. Our results provide a high-resolution roadmap for the transcription-factor-mediated reprogramming of human somatic cells, indicate a role for the trophectoderm-lineage-specific regulatory program during this process, and facilitate the direct reprogramming of somatic cells into induced trophoblast stem cells.

A single cell RNA sequencing resource for early sea urchin development

Identifying cell states during development from their mRNA profiles provides insight into their gene regulatory network. Here, we leverage the sea urchin embryo for its well-established gene regulatory network to interrogate the embryo using single cell RNA sequencing. We tested eight developmental stages in Strongylocentrotus purpuratus, from the eight-cell stage to late in gastrulation. We used these datasets to parse out 22 major cell states of the embryo, focusing on key transition stages for cell type specification of each germ layer. Subclustering of these major embryonic domains revealed over 50 cell states with distinct transcript profiles. Furthermore, we identified the transcript profile of two cell states expressing germ cell factors, one we conclude represents the primordial germ cells and the other state is transiently present during gastrulation. We hypothesize that these cells of the Veg2 tier of the early embryo represent a lineage that converts to the germ line when the primordial germ cells are deleted. This broad resource will hopefully enable the community to identify other cell states and genes of interest to expose the underpinning of developmental mechanisms.

A Similar Speciation Process Relying on Cellular Stochasticity in Microbial and Cancer Cell Populations

Similarities between microbial and cancer cells were noticed in recent years and serve as a basis for an atavism theory of cancer. Cancer cells would rely on the reactivation of an ancestral "genetic program" that would have been repressed in metazoan cells. Here we argue that cancer cells resemble unicellular organisms mainly in their similar way to exploit cellular stochasticity to produce cell specialization and maximize proliferation. Indeed, the relationship between low stochasticity, specialization, and quiescence found in normal differentiated metazoan cells is lost in cancer. On the contrary, low stochasticity and specialization are associated with high proliferation among cancer cells, as it is observed for the "specialist" cells in microbial populations that fully exploit nutritional resources to maximize proliferation. Thus, we propose a model where the appearance of cancer phenotypes can be solely due to an adaptation and a speciation process based on initial increase in cellular stochasticity.

Characterization of Diabetic and Non-Diabetic Foot Ulcers Using Single-Cell RNA-Sequencing

Background: Recent advances in high-throughput single-cell sequencing technologies have led to their increasingly widespread adoption for clinical applications. However, challenges associated with tissue viability, cell yield, and delayed time-to-capture have created unique obstacles for data processing. Chronic wounds, in particular, represent some of the most difficult target specimens, due to the significant amount of fibrinous debris, extracellular matrix components, and non-viable cells inherent in tissue routinely obtained from debridement. Methods: Here, we examined the feasibility of single cell RNA sequencing (scRNA-seq) analysis to evaluate human chronic wound samples acquired in the clinic, subjected to prolonged cold ischemia time, and processed without FACS sorting. Wound tissue from human diabetic and non-diabetic plantar foot ulcers were evaluated using an optimized 10X Genomics scRNA-seq platform and analyzed using a modified data pipeline designed for low-yield specimens. Cell subtypes were identified informatically and their distributions and transcriptional programs were compared between diabetic and non-diabetic tissue. Results: 139,000 diabetic and non-diabetic wound cells were delivered for 10X capture after either 90 or 180 min of cold ischemia time. cDNA library concentrations were 858.7 and 364.7 pg/µL, respectively, prior to sequencing. Among all barcoded fragments, we found that 83.5% successfully aligned to the human transcriptome and 68% met the minimum cell viability threshold. The average mitochondrial mRNA fraction was 8.5% for diabetic cells and 6.6% for non-diabetic cells, correlating with differences in cold ischemia time. A total of 384 individual cells were of sufficient quality for subsequent analyses; from this cell pool, we identified transcriptionally-distinct cell clusters whose gene expression profiles corresponded to fibroblasts, keratinocytes, neutrophils, monocytes, and endothelial cells. Fibroblast subpopulations with differing fibrotic potentials were identified, and their distributions were found to be altered in diabetic vs. non-diabetic cells. Conclusions: scRNA-seq of clinical wound samples can be achieved using minor modifications to standard processing protocols and data analysis methods. This simple approach can capture widespread transcriptional differences between diabetic and non-diabetic tissue obtained from matched wound locations.

Elucidating the fundamental fibrotic processes driving abdominal adhesion formation

Adhesions are fibrotic scars that form between abdominal organs following surgery or infection, and may cause bowel obstruction, chronic pain, or infertility. Our understanding of adhesion biology is limited, which explains the paucity of anti-adhesion treatments. Here we present a systematic analysis of mouse and human adhesion tissues. First, we show that adhesions derive primarily from the visceral peritoneum, consistent with our clinical experience that adhesions form primarily following laparotomy rather than laparoscopy. Second, adhesions are formed by poly-clonal proliferating tissue-resident fibroblasts. Third, using single cell RNA-sequencing, we identify heterogeneity among adhesion fibroblasts, which is more pronounced at early timepoints. Fourth, JUN promotes adhesion formation and results in upregulation of PDGFRA expression. With JUN suppression, adhesion formation is diminished. Our findings support JUN as a therapeutic target to prevent adhesions. An anti-JUN therapy that could be applied intra-operatively to prevent adhesion formation could dramatically improve the lives of surgical patients.

Inclusion of temporal information in single cell transcriptomics

Single cell transcriptomics has emerged as a powerful method for dissecting cell type diversity and for understanding mechanisms of cell fate decisions. However, inclusion of temporal information remains challenging, since each cell can be measured only once by sequencing analysis. Here, we discuss recent progress and current efforts towards inclusion of temporal information in single cell transcriptomics. Even from snapshot data, temporal dynamics can be computationally inferred via pseudo-temporal ordering of single cell transcriptomes. Temporal information can also come from analysis of intronic reads or from RNA metabolic labeling, which can provide additional evidence for pseudo-time trajectories and enable more fine-grained analysis of gene regulatory interactions. These approaches measure dynamics on short timescales of hours. Emerging methods for high-throughput lineage tracing now enable information storage over long timescales by using CRISPR/Cas9 to record information in the genome, which can later be read out by sequencing.