Stem cell dynamics and cellular heterogeneity across lineage subtypes of castrate-resistant prostate cancer.

To resist lineage-dependent therapies such as androgen receptor inhibition, prostate luminal epithelial adenocarcinoma cells often adopt a stem-like state resulting in lineage plasticity and phenotypic heterogeneity. Castrate-resistant prostate adenocarcinoma can transition to neuroendocrine (NE) and occasionally to amphicrine, co-expressed luminal and NE, phenotypes. We developed castrate-resistant prostate cancer (CRPC) patient-derived organoid models that preserve heterogeneity of the originating tumor, including an amphicrine model displaying a range of luminal and NE phenotypes. To gain biological insight and to identify potential treatment targets within heterogeneous tumor cell populations, we assessed the lineage hierarchy and molecular characteristics of various CRPC tumor subpopulations. Transcriptionally similar stem/progenitor (St/Pr) cells were identified for all lineage populations. Lineage tracing in amphicrine CRPC showed that heterogeneity originated from distinct subclones of infrequent St/Pr cells that produced mainly quiescent differentiated amphicrine progeny. By contrast, adenocarcinoma CRPC progeny originated from St/Pr cells and self-renewing differentiated luminal cells. Neuroendocrine prostate cancer (NEPC) was composed almost exclusively of self-renewing St/Pr cells. Amphicrine subpopulations were enriched for secretory luminal, mesenchymal, and enzalutamide treatment persistent signatures that characterize clinical progression. Finally, the amphicrine St/Pr subpopulation was specifically depleted with an AURKA inhibitor, which blocked tumor growth. These data illuminate distinct stem cell (SC) characteristics for subtype-specific CRPC in addition to demonstrating a context for targeting differentiation-competent prostate SCs.

Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes.

Complex gene regulatory mechanisms underlie differentiation and reprogramming. Contemporary single-cell lineage-tracing (scLT) methods use expressed, heritable DNA barcodes to combine cell lineage readout with single-cell transcriptomics. However, reliance on transcriptional profiling limits adaptation to other single-cell assays. With CellTag-multi, we present an approach that enables direct capture of heritable random barcodes expressed as polyadenylated transcripts, in both single-cell RNA sequencing and single-cell Assay for Transposase Accessible Chromatin using sequencing assays, allowing for independent clonal tracking of transcriptional and epigenomic cell states. We validate CellTag-multi to characterize progenitor cell lineage priming during mouse hematopoiesis. Additionally, in direct reprogramming of fibroblasts to endoderm progenitors, we identify core regulatory programs underlying on-target and off-target fates. Furthermore, we reveal the transcription factor Zfp281 as a regulator of reprogramming outcome, biasing cells toward an off-target mesenchymal fate. Our results establish CellTag-multi as a lineage-tracing method compatible with multiple single-cell modalities and demonstrate its utility in revealing fate-specifying gene regulatory changes across diverse paradigms of differentiation and reprogramming.

Defining cardiac functional recovery in end-stage heart failure at single-cell resolution.

Recovery of cardiac function is the holy grail of heart failure therapy yet is infrequently observed and remains poorly understood. In this study, we performed single-nucleus RNA sequencing from patients with heart failure who recovered left ventricular systolic function after left ventricular assist device implantation, patients who did not recover and non-diseased donors. We identified cell-specific transcriptional signatures of recovery, most prominently in macrophages and fibroblasts. Within these cell types, inflammatory signatures were negative predictors of recovery, and downregulation of RUNX1 was associated with recovery. In silico perturbation of RUNX1 in macrophages and fibroblasts recapitulated the transcriptional state of recovery. Cardiac recovery mediated by BET inhibition in mice led to decreased macrophage and fibroblast Runx1 expression and diminished chromatin accessibility within a Runx1 intronic peak and acquisition of human recovery signatures. These findings suggest that cardiac recovery is a unique biological state and identify RUNX1 as a possible therapeutic target to facilitate cardiac recovery.

Single-cell lineage tracing reveals hierarchy and mechanism of adipocyte precursor maturation.

White adipose tissue is crucial in various physiological processes. In response to high caloric intake, adipose tissue may expand by generating new adipocytes. Adipocyte precursor cells (progenitors and preadipocytes) are essential for generating mature adipocytes, and single-cell RNA sequencing provides new means to identify these populations. Here, we characterized adipocyte precursor populations in the skin, an adipose depot with rapid and robust generation of mature adipocytes. We identified a new population of immature preadipocytes, revealed a biased differentiation potential of progenitor cells, and identified Sox9 as a critical factor in driving progenitors toward adipose commitment, the first known mechanism of progenitor differentiation. These findings shed light on the specific dynamics and molecular mechanisms underlying rapid adipogenesis in the skin.

Dissecting cell identity via network inference and in silico gene perturbation.

Cell identity is governed by the complex regulation of gene expression, represented as gene-regulatory networks1. Here we use gene-regulatory networks inferred from single-cell multi-omics data to perform in silico transcription factor perturbations, simulating the consequent changes in cell identity using only unperturbed wild-type data. We apply this machine-learning-based approach, CellOracle, to well-established paradigms-mouse and human haematopoiesis, and zebrafish embryogenesis-and we correctly model reported changes in phenotype that occur as a result of transcription factor perturbation. Through systematic in silico transcription factor perturbation in the developing zebrafish, we simulate and experimentally validate a previously unreported phenotype that results from the loss of noto, an established notochord regulator. Furthermore, we identify an axial mesoderm regulator, lhx1a. Together, these results show that CellOracle can be used to analyse the regulation of cell identity by transcription factors, and can provide mechanistic insights into development and differentiation.

Gene regulatory network reconfiguration in direct lineage reprogramming.

In direct lineage conversion, transcription factor (TF) overexpression reconfigures gene regulatory networks (GRNs) to reprogram cell identity. We previously developed CellOracle, a computational method to infer GRNs from single-cell transcriptome and epigenome data. Using inferred GRNs, CellOracle simulates gene expression changes in response to TF perturbation, enabling in silico interrogation of network reconfiguration. Here, we combine CellOracle analysis with lineage tracing of fibroblast to induced endoderm progenitor (iEP) conversion, a prototypical direct reprogramming paradigm. By linking early network state to reprogramming outcome, we reveal distinct network configurations underlying successful and failed fate conversion. Via in silico simulation of TF perturbation, we identify new factors to coax cells into successfully converting their identity, uncovering a central role for the AP-1 subunit Fos with the Hippo signaling effector, Yap1. Together, these results demonstrate the efficacy of CellOracle to infer and interpret cell-type-specific GRN configurations, providing new mechanistic insights into lineage reprogramming.

The impact of AI on research.

Large and complex datasets have made artificial intelligence (AI) an invaluable tool for discovery across biological research. We asked experts how AI has impacted their work. Their experiences and perspectives offer thoughtful insights into potential offered by AI for their fields.

Anniversary reflections: Inspiring discoveries and the future of the field.

Cell Stem Cell was launched in 2007, and this year marks its 15th anniversary. To recognize this occasion, we asked six advisory board members to reflect on inspiring discoveries reported in Cell Stem Cell and how these breakthroughs connect to their vision for the future of the field.

Identification of a retinoic acid-dependent haemogenic endothelial progenitor from human pluripotent stem cells.

The generation of haematopoietic stem cells (HSCs) from human pluripotent stem cells (hPSCs) is a major goal for regenerative medicine. During embryonic development, HSCs derive from haemogenic endothelium (HE) in a NOTCH- and retinoic acid (RA)-dependent manner. Although a WNT-dependent (WNTd) patterning of nascent hPSC mesoderm specifies clonally multipotent intra-embryonic-like HOXA+ definitive HE, this HE is functionally unresponsive to RA. Here we show that WNTd mesoderm, before HE specification, is actually composed of two distinct KDR+ CD34neg populations. CXCR4negCYP26A1+ mesoderm gives rise to HOXA+ multilineage definitive HE in an RA-independent manner, whereas CXCR4+ ALDH1A2+ mesoderm gives rise to HOXA+ multilineage definitive HE in a stage-specific, RA-dependent manner. Furthermore, both RA-independent (RAi) and RA-dependent (RAd) HE harbour transcriptional similarity to distinct populations found in the early human embryo, including HSC-competent HE. This revised model of human haematopoietic development provides essential resolution to the regulation and origins of the multiple waves of haematopoiesis. These insights provide the basis for the generation of specific haematopoietic populations, including the de novo specification of HSCs.

Capybara: A computational tool to measure cell identity and fate transitions.

Measuring cell identity in development, disease, and reprogramming is challenging as cell types and states are in continual transition. Here, we present Capybara, a computational tool to classify discrete cell identity and intermediate "hybrid" cell states, supporting a metric to quantify cell fate transition dynamics. We validate hybrid cells using experimental lineage tracing data to demonstrate the multi-lineage potential of these intermediate cell states. We apply Capybara to diagnose shortcomings in several cell engineering protocols, identifying hybrid states in cardiac reprogramming and off-target identities in motor neuron programming, which we alleviate by adding exogenous signaling factors. Further, we establish a putative in vivo correlate for induced endoderm progenitors. Together, these results showcase the utility of Capybara to dissect cell identity and fate transitions, prioritizing interventions to enhance the efficiency and fidelity of stem cell engineering.

Single cell biology-a Keystone Symposia report.

Single cell biology has the potential to elucidate many critical biological processes and diseases, from development and regeneration to cancer. Single cell analyses are uncovering the molecular diversity of cells, revealing a clearer picture of the variation among and between different cell types. New techniques are beginning to unravel how differences in cell state-transcriptional, epigenetic, and other characteristics-can lead to different cell fates among genetically identical cells, which underlies complex processes such as embryonic development, drug resistance, response to injury, and cellular reprogramming. Single cell technologies also pose significant challenges relating to processing and analyzing vast amounts of data collected. To realize the potential of single cell technologies, new computational approaches are needed. On March 17-19, 2021, experts in single cell biology met virtually for the Keystone eSymposium "Single Cell Biology" to discuss advances both in single cell applications and technologies.

Basal epithelial stem cells cross an alarmin checkpoint for postviral lung disease.

Epithelial cells are charged with protection at barrier sites, but whether this normally beneficial response might sometimes become dysfunctional still needs definition. Here, we recognized a pattern of imbalance marked by basal epithelial cell growth and differentiation that replaced normal airspaces in a mouse model of progressive postviral lung disease due to the Sendai virus. Single-cell and lineage-tracing technologies identified a distinct subset of basal epithelial stem cells (basal ESCs) that extended into gas-exchange tissue to form long-term bronchiolar-alveolar remodeling regions. Moreover, this cell subset was selectively expanded by crossing a cell-growth and survival checkpoint linked to the nuclear-localized alarmin IL-33 that was independent of IL-33 receptor signaling and instead connected to autocrine chromatin accessibility. This mechanism creates an activated stem-progenitor cell lineage with potential for physiological or pathological function. Thus, conditional loss of Il33 gene function in basal epithelial cells disrupted the homeostasis of the epithelial barrier at skin and gut sites but also markedly attenuated postviral disease in the lung based on the downregulation of remodeling and inflammation. Thus, we define a basal ESC strategy to deploy innate immune machinery that appears to overshoot the primordial goal of self-defense. Our findings reveal new targets to stratify and correct chronic and often deadly postviral disease.

The coding and long noncoding single-cell atlas of the developing human fetal striatum.

Deciphering how the human striatum develops is necessary for understanding the diseases that affect this region. To decode the transcriptional modules that regulate this structure during development, we compiled a catalog of 1116 long intergenic noncoding RNAs (lincRNAs) identified de novo and then profiled 96,789 single cells from the early human fetal striatum. We found that D1 and D2 medium spiny neurons (D1- and D2-MSNs) arise from a common progenitor and that lineage commitment is established during the postmitotic transition, across a pre-MSN phase that exhibits a continuous spectrum of fate determinants. We then uncovered cell type-specific gene regulatory networks that we validated through in silico perturbation. Finally, we identified human-specific lincRNAs that contribute to the phylogenetic divergence of this structure in humans. This work delineates the cellular hierarchies governing MSN lineage commitment.

Gene expression dynamics underlying cell fate emergence in 2D micropatterned human embryonic stem cell gastruloids.

Human embryonic stem cells cultured in 2D micropatterns with BMP4 differentiate into a radial arrangement of germ layers and extraembryonic cells. Single-cell transcriptomes demonstrate generation of cell types transcriptionally similar to their in vivo counterparts in Carnegie stage 7 human gastrula. Time-course analyses indicate sequential differentiation, where the epiblast arises by 12 h between the prospective ectoderm in the center and the cells initiating differentiation toward extraembryonic fates at the edge. Extraembryonic and mesendoderm precursors arise from the epiblast by 24 h, while nascent mesoderm, endoderm, and primordial germ cell-like cells form by 44 h. Dynamic changes in transcripts encoding signaling components support a BMP, WNT, and Nodal hierarchy underlying germ-layer specification conserved across mammals, and FGF and HIPPO pathways being active throughout differentiation. This work also provides a resource for mining genes and pathways expressed in a stereotyped 2D gastruloid model, common with other species or unique to human gastrulation.

Localized EMT reprograms glial progenitors to promote spinal cord repair.

Anti-regenerative scarring obstructs spinal cord repair in mammals and presents a major hurdle for regenerative medicine. In contrast, adult zebrafish possess specialized glial cells that spontaneously repair spinal cord injuries by forming a pro-regenerative bridge across the severed tissue. To identify the mechanisms that regulate differential regenerative capacity between mammals and zebrafish, we first defined the molecular identity of zebrafish bridging glia and then performed cross-species comparisons with mammalian glia. Our transcriptomics show that pro-regenerative zebrafish glia activate an epithelial-to-mesenchymal transition (EMT) gene program and that EMT gene expression is a major factor distinguishing mammalian and zebrafish glia. Functionally, we found that localized niches of glial progenitors undergo EMT after spinal cord injury in zebrafish and, using large-scale CRISPR-Cas9 mutagenesis, we identified the gene regulatory network that activates EMT and drives functional regeneration. Thus, non-regenerative mammalian glia lack an essential EMT-driving gene regulatory network that reprograms pro-regenerative zebrafish glia after injury.

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.

Deconstructing Stepwise Fate Conversion of Human Fibroblasts to Neurons by MicroRNAs.

Cell-fate conversion generally requires reprogramming effectors to both introduce fate programs of the target cell type and erase the identity of starting cell population. Here, we reveal insights into the activity of microRNAs miR-9/9∗ and miR-124 (miR-9/9∗-124) as reprogramming agents that orchestrate direct conversion of human fibroblasts into motor neurons by first eradicating fibroblast identity and promoting uniform transition to a neuronal state in sequence. We identify KLF-family transcription factors as direct target genes for miR-9/9∗-124 and show their repression is critical for erasing fibroblast fate. Subsequent gain of neuronal identity requires upregulation of a small nuclear RNA, RN7SK, which induces accessibilities of chromatin regions and neuronal gene activation to push cells to a neuronal state. Our study defines deterministic components in the microRNA-mediated reprogramming cascade.

Next-Generation Lineage Tracing and Fate Mapping to Interrogate Development.

Lineage tracing and fate mapping, overlapping yet distinct disciplines to follow cells and their progeny, have evolved rapidly over the last century. Lineage tracing aims to identify all progeny arising from an individual cell, placing them within a lineage hierarchy. The recent emergence of genomic technologies, such as single-cell and spatial transcriptomics, has fostered sophisticated new methods to reconstruct lineage relationships at high resolution. In contrast, fate maps, schematics showing which parts of the embryo will develop into which tissue, have remained relatively static since the 1970s. However, fate maps provide spatial information, often lost in lineage reconstruction, that can offer fundamental mechanistic insight into development. Here, we broadly review the origins of fate mapping and lineage tracing approaches. We focus on the most recent developments in lineage tracing, permitted by advances in single-cell genomics. Finally, we explore the current potential to leverage these new technologies to synthesize high-resolution fate maps and discuss their potential for interrogating development at new depths.