A mouse model with high clonal barcode diversity for joint lineage, transcriptomic, and epigenomic profiling in single cells.

Cellular lineage histories and their molecular states encode fundamental principles of tissue development and homeostasis. Current lineage-recording mouse models have insufficient barcode diversity and single-cell lineage coverage for profiling tissues composed of millions of cells. Here, we developed DARLIN, an inducible Cas9 barcoding mouse line that utilizes terminal deoxynucleotidyl transferase (TdT) and 30 CRISPR target sites. DARLIN is inducible, generates massive lineage barcodes across tissues, and enables the detection of edited barcodes in ∼70% of profiled single cells. Using DARLIN, we examined fate bias within developing hematopoietic stem cells (HSCs) and revealed unique features of HSC migration. Additionally, we established a protocol for joint transcriptomic and epigenomic single-cell measurements with DARLIN and found that cellular clonal memory is associated with genome-wide DNA methylation rather than gene expression or chromatin accessibility. DARLIN will enable the high-resolution study of lineage relationships and their molecular signatures in diverse tissues and physiological contexts.

A neutrophil response linked to tumor control in immunotherapy.

Neutrophils accumulate in solid tumors, and their abundance correlates with poor prognosis. Neutrophils are not homogeneous, however, and could play different roles in cancer therapy. Here, we investigate the role of neutrophils in immunotherapy, leading to tumor control. We show that successful therapies acutely expanded tumor neutrophil numbers. This expansion could be attributed to a Sellhi state rather than to other neutrophils that accelerate tumor progression. Therapy-elicited neutrophils acquired an interferon gene signature, also seen in human patients, and appeared essential for successful therapy, as loss of the interferon-responsive transcription factor IRF1 in neutrophils led to failure of immunotherapy. The neutrophil response depended on key components of anti-tumor immunity, including BATF3-dependent DCs, IL-12, and IFNγ. In addition, we found that a therapy-elicited systemic neutrophil response positively correlated with disease outcome in lung cancer patients. Thus, we establish a crucial role of a neutrophil state in mediating effective cancer therapy.

Single-cell gene expression reveals a landscape of regulatory T cell phenotypes shaped by the TCR.

CD4+ T regulatory cells (Treg) are central to immune homeostasis, their phenotypic heterogeneity reflecting the diverse environments and target cells that they regulate. To understand this heterogeneity, we combined single-cell RNA-seq, activation reporter and T cell receptor (TCR) analysis to profile thousands of Treg or conventional CD4+FoxP3- T cells (Tconv) from mouse lymphoid organs and human blood. Treg and Tconv pools showed areas of overlap, as resting 'furtive' Tregs with overall similarity to Tconvs or as a convergence of activated states. All Tregs expressed a small core of FoxP3-dependent transcripts, onto which additional programs were added less uniformly. Among suppressive functions, Il2ra and Ctla4 were quasiconstant, inhibitory cytokines being more sparsely distributed. TCR signal intensity did not affect resting/activated Treg proportions but molded activated Treg programs. The main lines of Treg heterogeneity in mice were strikingly conserved in human blood. These results reveal unexpected TCR-shaped states of activation, providing a framework to synthesize previous observations of Treg heterogeneity.

Publisher Correction: Single-cell gene expression reveals a landscape of regulatory T cell phenotypes shaped by the TCR.

In the version of this article initially published, the Supplementary Note was missing. The Supplementary Note has now been provided online and is cited in the Methods section of the article. The error has been corrected in the HTML and PDF version of the article.

Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.

It has long been the dream of biologists to map gene expression at the single-cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways. Recently, RNA sequencing has achieved single-cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after leukemia inhibitory factor (LIF) withdrawal. The reproducibility of these high-throughput single-cell data allowed us to deconstruct cell populations and infer gene expression relationships. VIDEO ABSTRACT.

Single-Cell Transcriptomics of Human and Mouse Lung Cancers Reveals Conserved Myeloid Populations across Individuals and Species.

Tumor-infiltrating myeloid cells (TIMs) comprise monocytes, macrophages, dendritic cells, and neutrophils, and have emerged as key regulators of cancer growth. These cells can diversify into a spectrum of states, which might promote or limit tumor outgrowth but remain poorly understood. Here, we used single-cell RNA sequencing (scRNA-seq) to map TIMs in non-small-cell lung cancer patients. We uncovered 25 TIM states, most of which were reproducibly found across patients. To facilitate translational research of these populations, we also profiled TIMs in mice. In comparing TIMs across species, we identified a near-complete congruence of population structures among dendritic cells and monocytes; conserved neutrophil subsets; and species differences among macrophages. By contrast, myeloid cell population structures in patients' blood showed limited overlap with those of TIMs. This study determines the lung TIM landscape and sets the stage for future investigations into the potential of TIMs as immunotherapy targets.

Lineage tracing meets single-cell omics: opportunities and challenges.

A fundamental goal of developmental and stem cell biology is to map the developmental history (ontogeny) of differentiated cell types. Recent advances in high-throughput single-cell sequencing technologies have enabled the construction of comprehensive transcriptional atlases of adult tissues and of developing embryos from measurements of up to millions of individual cells. Parallel advances in sequencing-based lineage-tracing methods now facilitate the mapping of clonal relationships onto these landscapes and enable detailed comparisons between molecular and mitotic histories. Here we review recent progress and challenges, as well as the opportunities that emerge when these two complementary representations of cellular history are synthesized into integrated models of cell differentiation.

The emergence of transcriptional identity in somatosensory neurons.

More than twelve morphologically and physiologically distinct subtypes of primary somatosensory neuron report salient features of our internal and external environments1-4. It is unclear how specialized gene expression programs emerge during development to endow these subtypes with their unique properties. To assess the developmental progression of transcriptional maturation of each subtype of principal somatosensory neuron, we generated a transcriptomic atlas of cells traversing the primary somatosensory neuron lineage in mice. Here we show that somatosensory neurogenesis gives rise to neurons in a transcriptionally unspecialized state, characterized by co-expression of transcription factors that become restricted to select subtypes as development proceeds. Single-cell transcriptomic analyses of sensory neurons from mutant mice lacking transcription factors suggest that these broad-to-restricted transcription factors coordinate subtype-specific gene expression programs in subtypes in which their expression is maintained. We also show that neuronal targets are involved in this process; disruption of the prototypic target-derived neurotrophic factor NGF leads to aberrant subtype-restricted patterns of transcription factor expression. Our findings support a model in which cues that emanate from intermediate and final target fields promote neuronal diversification in part by transitioning cells from a transcriptionally unspecialized state to transcriptionally distinct subtypes by modulating the selection of subtype-restricted transcription factors.

Single-cell lineage tracing unveils a role for TCF15 in haematopoiesis.

Bone marrow transplantation therapy relies on the life-long regenerative capacity of haematopoietic stem cells (HSCs)1,2. HSCs present a complex variety of regenerative behaviours at the clonal level, but the mechanisms underlying this diversity are still undetermined3-11. Recent advances in single-cell RNA sequencing have revealed transcriptional differences among HSCs, providing a possible explanation for their functional heterogeneity12-17. However, the destructive nature of sequencing assays prevents simultaneous observation of stem cell state and function. To solve this challenge, we implemented expressible lentiviral barcoding, which enabled simultaneous analysis of lineages and transcriptomes from single adult HSCs and their clonal trajectories during long-term bone marrow reconstitution. Analysis of differential gene expression between clones with distinct behaviour revealed an intrinsic molecular signature that characterizes functional long-term repopulating HSCs. Probing this signature through in vivo CRISPR screening, we found the transcription factor TCF15 to be required and sufficient to drive HSC quiescence and long-term self-renewal. In situ, Tcf15 expression labels the most primitive subset of true multipotent HSCs. In conclusion, our work elucidates clone-intrinsic molecular programmes associated with functional stem cell heterogeneity and identifies a mechanism for the maintenance of the self-renewing HSC state.

Intestinal crypt homeostasis results from neutral competition between symmetrically dividing Lgr5 stem cells.

Intestinal stem cells, characterized by high Lgr5 expression, reside between Paneth cells at the small intestinal crypt base and divide every day. We have carried out fate mapping of individual stem cells by generating a multicolor Cre-reporter. As a population, Lgr5(hi) stem cells persist life-long, yet crypts drift toward clonality within a period of 1-6 months. We have collected short- and long-term clonal tracing data of individual Lgr5(hi) cells. These reveal that most Lgr5(hi) cell divisions occur symmetrically and do not support a model in which two daughter cells resulting from an Lgr5(hi) cell division adopt divergent fates (i.e., one Lgr5(hi) cell and one transit-amplifying [TA] cell per division). The cellular dynamics are consistent with a model in which the resident stem cells double their numbers each day and stochastically adopt stem or TA fates. Quantitative analysis shows that stem cell turnover follows a pattern of neutral drift dynamics.

Population snapshots predict early haematopoietic and erythroid hierarchies.

The formation of red blood cells begins with the differentiation of multipotent haematopoietic progenitors. Reconstructing the steps of this differentiation represents a general challenge in stem-cell biology. Here we used single-cell transcriptomics, fate assays and a theory that allows the prediction of cell fates from population snapshots to demonstrate that mouse haematopoietic progenitors differentiate through a continuous, hierarchical structure into seven blood lineages. We uncovered coupling between the erythroid and the basophil or mast cell fates, a global haematopoietic response to erythroid stress and novel growth factor receptors that regulate erythropoiesis. We defined a flow cytometry sorting strategy to purify early stages of erythroid differentiation, completely isolating classically defined burst-forming and colony-forming progenitors. We also found that the cell cycle is progressively remodelled during erythroid development and during a sharp transcriptional switch that ends the colony-forming progenitor stage and activates terminal differentiation. Our work showcases the utility of linking transcriptomic data to predictive fate models, and provides insights into lineage development in vivo.

A single-cell atlas of the airway epithelium reveals the CFTR-rich pulmonary ionocyte.

The functions of epithelial tissues are dictated by the types, abundance and distribution of the differentiated cells they contain. Attempts to restore tissue function after damage require knowledge of how physiological tasks are distributed among cell types, and how cell states vary between homeostasis, injury-repair and disease. In the conducting airway, a heterogeneous basal cell population gives rise to specialized luminal cells that perform mucociliary clearance1. Here we perform single-cell profiling of human bronchial epithelial cells and mouse tracheal epithelial cells to obtain a comprehensive census of cell types in the conducting airway and their behaviour in homeostasis and regeneration. Our analysis reveals cell states that represent known and novel cell populations, delineates their heterogeneity and identifies distinct differentiation trajectories during homeostasis and tissue repair. Finally, we identified a novel, rare cell type that we call the 'pulmonary ionocyte', which co-expresses FOXI1, multiple subunits of the vacuolar-type H+-ATPase (V-ATPase) and CFTR, the gene that is mutated in cystic fibrosis. Using immunofluorescence, modulation of signalling pathways and electrophysiology, we show that Notch signalling is necessary and FOXI1 expression is sufficient to drive the production of the pulmonary ionocyte, and that the pulmonary ionocyte is a major source of CFTR activity in the conducting airway epithelium.

Clonal analysis of lineage fate in native haematopoiesis.

Haematopoiesis, the process of mature blood and immune cell production, is functionally organized as a hierarchy, with self-renewing haematopoietic stem cells and multipotent progenitor cells sitting at the very top. Multiple models have been proposed as to what the earliest lineage choices are in these primitive haematopoietic compartments, the cellular intermediates, and the resulting lineage trees that emerge from them. Given that the bulk of studies addressing lineage outcomes have been performed in the context of haematopoietic transplantation, current models of lineage branching are more likely to represent roadmaps of lineage potential than native fate. Here we use transposon tagging to clonally trace the fates of progenitors and stem cells in unperturbed haematopoiesis. Our results describe a distinct clonal roadmap in which the megakaryocyte lineage arises largely independently of other haematopoietic fates. Our data, combined with single-cell RNA sequencing, identify a functional hierarchy of unilineage- and oligolineage-producing clones within the multipotent progenitor population. Finally, our results demonstrate that traditionally defined long-term haematopoietic stem cells are a significant source of megakaryocyte-restricted progenitors, suggesting that the megakaryocyte lineage is the predominant native fate of long-term haematopoietic stem cells. Our study provides evidence for a substantially revised roadmap for unperturbed haematopoiesis, and highlights unique properties of multipotent progenitors and haematopoietic stem cells in situ.

Lineage reconstruction from clonal correlations.

A central task in developmental biology is to learn the sequence of fate decisions that leads to each mature cell type in a tissue or organism. Recently, clonal labeling of cells using DNA barcodes has emerged as a powerful approach for identifying cells that share a common ancestry of fate decisions. Here we explore the idea that stochasticity of cell fate choice during tissue development could be harnessed to read out lineage relationships after a single step of clonal barcoding. By considering a generalized multitype branching process, we determine the conditions under which the final distribution of barcodes over observed cell types encodes their bona fide lineage relationships. We then propose a method for inferring the order of fate decisions. Our theory predicts a set of symmetries of barcode covariance that serves as a consistency check for the validity of the method. We show that broken symmetries may be used to detect multiple paths of differentiation to the same cell types. We provide computational tools for general use. When applied to barcoding data in hematopoiesis, these tools reconstruct the classical hematopoietic hierarchy and detect couplings between monocytes and dendritic cells and between erythrocytes and basophils that suggest multiple pathways of differentiation for these lineages.

Fundamental limits on dynamic inference from single-cell snapshots.

Single-cell expression profiling reveals the molecular states of individual cells with unprecedented detail. Because these methods destroy cells in the process of analysis, they cannot measure how gene expression changes over time. However, some information on dynamics is present in the data: the continuum of molecular states in the population can reflect the trajectory of a typical cell. Many methods for extracting single-cell dynamics from population data have been proposed. However, all such attempts face a common limitation: for any measured distribution of cell states, there are multiple dynamics that could give rise to it, and by extension, multiple possibilities for underlying mechanisms of gene regulation. Here, we describe the aspects of gene expression dynamics that cannot be inferred from a static snapshot alone and identify assumptions necessary to constrain a unique solution for cell dynamics from static snapshots. We translate these constraints into a practical algorithmic approach, population balance analysis (PBA), which makes use of a method from spectral graph theory to solve a class of high-dimensional differential equations. We use simulations to show the strengths and limitations of PBA, and then apply it to single-cell profiles of hematopoietic progenitor cells (HPCs). Cell state predictions from this analysis agree with HPC fate assays reported in several papers over the past two decades. By highlighting the fundamental limits on dynamic inference faced by any method, our framework provides a rigorous basis for dynamic interpretation of a gene expression continuum and clarifies best experimental designs for trajectory reconstruction from static snapshot measurements.

Proteomics of phosphorylation and protein dynamics during fertilization and meiotic exit in the Xenopus egg.

Fertilization releases the meiotic arrest and initiates the events that prepare the egg for the ensuing developmental program. Protein degradation and phosphorylation are known to regulate protein activity during this process. However, the full extent of protein loss and phosphoregulation is still unknown. We examined absolute protein and phosphosite dynamics of the fertilization response by mass spectrometry-based proteomics in electroactivated eggs. To do this, we developed an approach for calculating the stoichiometry of phosphosites from multiplexed proteomics that is compatible with dynamic, stable, and multisite phosphorylation. Overall, the data suggest that degradation is limited to a few low-abundance proteins. However, this degradation promotes extensive dephosphorylation that occurs over a wide range of abundances during meiotic exit. We also show that eggs release a large amount of protein into the medium just after fertilization, most likely related to the blocks to polyspermy. Concomitantly, there is a substantial increase in phosphorylation likely tied to calcium-activated kinases. We identify putative degradation targets and components of the slow block to polyspermy. The analytical approaches demonstrated here are broadly applicable to studies of dynamic biological systems.

SPRING: a kinetic interface for visualizing high dimensional single-cell expression data.

Motivation: Single-cell gene expression profiling technologies can map the cell states in a tissue or organism. As these technologies become more common, there is a need for computational tools to explore the data they produce. In particular, visualizing continuous gene expression topologies can be improved, since current tools tend to fragment gene expression continua or capture only limited features of complex population topologies. Results: Force-directed layouts of k-nearest-neighbor graphs can visualize continuous gene expression topologies in a manner that preserves high-dimensional relationships and captures complex population topologies. We describe SPRING, a pipeline for data filtering, normalization and visualization using force-directed layouts and show that it reveals more detailed biological relationships than existing approaches when applied to branching gene expression trajectories from hematopoietic progenitor cells and cells of the upper airway epithelium. Visualizations from SPRING are also more reproducible than those of stochastic visualization methods such as tSNE, a state-of-the-art tool. We provide SPRING as an interactive web-tool with an easy to use GUI. Availability and implementation: https://kleintools.hms.harvard.edu/tools/spring.html, https://github.com/AllonKleinLab/SPRING/. Contact: calebsw@gmail.com or allon_klein@hms.harvard.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

The critical discussion group: fostering personal and scientific growth.

As scientists, we greatly benefit from discussing our work with our peers. Informal, unstructured interactions often yield highly creative feedback. With this in mind, we created a group that fosters discussion of its members' work. The group engages us in new research fields and ways of thinking, and provides us with an opportunity for co-mentoring. Three key components were essential for making this group work: the emphasis on non-hierarchical debate; the diversity of the group members; and the mutual respect existing among the participants.