A computational tool suite to facilitate single-cell lineage tracing analyses.

Tracking the lineage relationships of cell populations is of increasing interest in diverse biological contexts. In this issue of Cell Reports Methods, Holze et al. present a suite of computational tools to facilitate such analyses and encourage their broader application.

Extracting, filtering and simulating cellular barcodes using CellBarcode tools.

Identifying true DNA cellular barcodes among polymerase chain reaction and sequencing errors is challenging. Current tools are restricted in the diversity of barcode types supported or the analysis strategies implemented. As such, there is a need for more versatile and efficient tools for barcode extraction, as well as for tools to investigate which factors impact barcode detection and which filtering strategies to best apply. Here we introduce the package CellBarcode and its barcode simulation kit, CellBarcodeSim, that allows efficient and versatile barcode extraction and filtering for a range of barcode types from bulk or single-cell sequencing data using a variety of filtering strategies. Using the barcode simulation kit and biological data, we explore the technical and biological factors influencing barcode identification and provide a decision tree on how to optimize barcode identification for different barcode settings. We believe that CellBarcode and CellBarcodeSim have the capability to enhance the reproducibility and interpretation of barcode results across studies.

Breast cancer remotely imposes a myeloid bias on haematopoietic stem cells by reprogramming the bone marrow niche.

Myeloid cell infiltration of solid tumours generally associates with poor patient prognosis and disease severity1-13. Therefore, understanding the regulation of myeloid cell differentiation during cancer is crucial to counteract their pro-tumourigenic role. Bone marrow (BM) haematopoiesis is a tightly regulated process for the production of all immune cells in accordance to tissue needs14. Myeloid cells differentiate during haematopoiesis from multipotent haematopoietic stem and progenitor cells (HSPCs)15-17. HSPCs can sense inflammatory signals from the periphery during infections18-21 or inflammatory disorders22-27. In these settings, HSPC expansion is associated with increased myeloid differentiation28,29. During carcinogenesis, the elevation of haematopoietic growth factors supports the expansion and differentiation of committed myeloid progenitors5,30. However, it is unclear whether cancer-related inflammation also triggers demand-adapted haematopoiesis at the level of multipotent HSPCs. In the BM, HSPCs reside within the haematopoietic niche which delivers HSC maintenance and differentiation cues31-35. Mesenchymal stem cells (MSCs) are a major cellular component of the BM niche and contribute to HSC homeostasis36-41. Modifications of MSCs in systemic disorders have been associated with HSC differentiation towards myeloid cells22,42. It is unknown if MSCs are regulated in the context of solid tumours and if their myeloid supportive activity is impacted by cancer-induced systemic changes. Here, using unbiased transcriptomic analysis and in situ imaging of HSCs and the BM niche during breast cancer, we show that both HSCs and MSCs are transcriptionally and spatially modified. We demonstrate that breast tumour can distantly remodel the cellular cross-talks in the BM niche leading to increased myelopoiesis.

DRAG in situ barcoding reveals an increased number of HSPCs contributing to myelopoiesis with age.

Ageing is associated with changes in the cellular composition of the immune system. During ageing, hematopoietic stem and progenitor cells (HSPCs) that produce immune cells are thought to decline in their regenerative capacity. However, HSPC function has been mostly assessed using transplantation assays, and it remains unclear how HSPCs age in the native bone marrow niche. To address this issue, we present an in situ single cell lineage tracing technology to quantify the clonal composition and cell production of single cells in their native niche. Our results demonstrate that a pool of HSPCs with unequal output maintains myelopoiesis through overlapping waves of cell production throughout adult life. During ageing, the increased frequency of myeloid cells is explained by greater numbers of HSPCs contributing to myelopoiesis rather than the increased myeloid output of individual HSPCs. Strikingly, the myeloid output of HSPCs remains constant over time despite accumulating significant transcriptomic changes throughout adulthood. Together, these results show that, unlike emergency myelopoiesis post-transplantation, aged HSPCs in their native microenvironment do not functionally decline in their regenerative capacity.

Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells.

Few techniques can assess phenotype and fate for the same cell simultaneously. Most of the current protocols used to characterize phenotype, although able to generate large datasets, necessitate the destruction of the cell of interest, making it impossible to assess its functional fate. Heterogeneous biological differentiating systems like hematopoiesis are therefore difficult to describe. Building on cell division tracking dyes, we further developed a protocol to simultaneously determine kinship, division number, and differentiation status for many single hematopoietic progenitors. This protocol allows the assessment of the ex vivo differentiation potential of murine and human hematopoietic progenitors, isolated from various biological sources. Moreover, as it is based on flow cytometry and a limited number of reagents, it can quickly generate a large amount of data, at the single-cell level, in a relatively inexpensive manner. We also provide the analytical pipeline for single-cell analysis, combined with a robust statistical framework. As this protocol allows the linking of cell division and differentiation at the single-cell level, it can be used to quantitatively assess symmetric and asymmetric fate commitment, the balance between self-renewal and differentiation, and the number of divisions for a given commitment fate. Altogether, this protocol can be used in experimental designs aiming to unravel the biological differences between hematopoietic progenitors, from a single-cell perspective.

CellDestiny: A RShiny application for the visualization and analysis of single-cell lineage tracing data.

Single-cell lineage tracing permits the labeling of individual cells with a heritable marker to follow the fate of each cell's progeny. Over the last twenty years, several single-cell lineage tracing methods have emerged, enabling major discoveries in developmental biology, oncology and gene therapies. Analytical tools are needed to draw meaningful conclusions from lineage tracing measurements, which are characterized by high variability, sparsity and technical noise. However, the single cell lineage tracing field lacks versatile and easy-to-use tools for standardized and reproducible analyses, in particular tools accessible to biologists. Here we present CellDestiny, a RShiny app and associated web application developed for experimentalists without coding skills to perform visualization and analysis of single cell lineage-tracing datasets through a graphical user interface. We demonstrate the functionality of CellDestiny through the analysis of (i) lentiviral barcoding datasets of murine hematopoietic progenitors; (ii) published integration site data from Wiskott-Aldrich Symdrome patients undergoing gene-therapy treatment; and (iii) simultaneous barcoding and transcriptomic analysis of murine hematopoietic progenitor differentiation in vitro. In summary, CellDestiny is an easy-to-use and versatile toolkit that enables biologists to visualize and analyze single-cell lineage tracing data.

H3K27me3 conditions chemotolerance in triple-negative breast cancer.

The persistence of cancer cells resistant to therapy remains a major clinical challenge. In triple-negative breast cancer, resistance to chemotherapy results in the highest recurrence risk among breast cancer subtypes. The drug-tolerant state seems largely defined by nongenetic features, but the underlying mechanisms are poorly understood. Here, by monitoring epigenomes, transcriptomes and lineages with single-cell resolution, we show that the repressive histone mark H3K27me3 (trimethylation of histone H3 at lysine 27) regulates cell fate at the onset of chemotherapy. We report that a persister expression program is primed with both H3K4me3 (trimethylation of histone H3 at lysine 4) and H3K27me3 in unchallenged cells, with H3K27me3 being the lock to its transcriptional activation. We further demonstrate that depleting H3K27me3 enhances the potential of cancer cells to tolerate chemotherapy. Conversely, preventing H3K27me3 demethylation simultaneously to chemotherapy inhibits the transition to a drug-tolerant state, and delays tumor recurrence in vivo. Our results highlight how chromatin landscapes shape the potential of cancer cells to respond to initial therapy.

Replicative history marks transcriptional and functional disparity in the CD8+ T cell memory pool.

Clonal expansion is a core aspect of T cell immunity. However, little is known with respect to the relationship between replicative history and the formation of distinct CD8+ memory T cell subgroups. To address this issue, we developed a genetic-tracing approach, termed the DivisionRecorder, that reports the extent of past proliferation of cell pools in vivo. Using this system to genetically 'record' the replicative history of different CD8+ T cell populations throughout a pathogen-specific immune response, we demonstrate that the central memory T (TCM) cell pool is marked by a higher number of prior divisions than the effector memory T cell pool, owing to the combination of strong proliferative activity during the acute immune response and selective proliferative activity after pathogen clearance. Furthermore, by combining DivisionRecorder analysis with single-cell transcriptomics and functional experiments, we show that replicative history identifies distinct cell pools within the TCM compartment. Specifically, we demonstrate that lowly divided TCM cells display enriched expression of stem-cell-associated genes, exist in a relatively quiescent state, and are superior in eliciting a proliferative recall response upon activation. These data provide the first evidence that a stem-cell-like memory T cell pool that reconstitutes the CD8+ T cell effector pool upon reinfection is marked by prior quiescence.

In Vivo Monitoring of Polycythemia Vera Development Reveals Carbonic Anhydrase 1 as a Potent Therapeutic Target.

Current murine models of myeloproliferative neoplasms (MPNs) cannot examine how MPNs progress from a single bone marrow source to the entire hematopoietic system. Thus, using transplantation of knock-in JAK2V617F hematopoietic cells into a single irradiated leg, we show development of polycythemia vera (PV) from a single anatomic site in immunocompetent mice. Barcode experiments reveal that grafted JAK2V617F stem/progenitor cells migrate from the irradiated leg to nonirradiated organs such as the contralateral leg and spleen, which is strictly required for development of PV. Mutant cells colonizing the nonirradiated leg efficiently induce PV in nonconditioned recipient mice and contain JAK2V617F hematopoietic stem/progenitor cells that express high levels of carbonic anhydrase 1 (CA1), a peculiar feature also found in CD34+ cells from patients with PV. Finally, genetic and pharmacologic inhibition of CA1 efficiently suppresses PV development and progression in mice and decreases PV patients' erythroid progenitors, strengthening CA1 as a potent therapeutic target for PV. SIGNIFICANCE: Follow-up of hematopoietic malignancies from their initiating anatomic site is crucial for understanding their development and discovering new therapeutic avenues. We developed such an approach, used it to characterize PV progression, and identified CA1 as a promising therapeutic target of PV. This article is highlighted in the In This Issue feature, p. 265.

Erythropoietin directly remodels the clonal composition of murine hematopoietic multipotent progenitor cells.

The cytokine erythropoietin (EPO) is a potent inducer of erythrocyte development and one of the most prescribed biopharmaceuticals. The action of EPO on erythroid progenitor cells is well established, but its direct action on hematopoietic stem and progenitor cells (HSPCs) is still debated. Here, using cellular barcoding, we traced the differentiation of hundreds of single murine HSPCs, after ex vivo EPO exposure and transplantation, in five different hematopoietic cell lineages, and observed the transient occurrence of high-output myeloid-erythroid-megakaryocyte-biased and myeloid-B-cell-dendritic cell-biased clones. Single-cell RNA sequencing analysis of ex vivo EPO-exposed HSPCs revealed that EPO induced the upregulation of erythroid associated genes in a subset of HSPCs, overlapping with multipotent progenitor (MPP) 1 and MPP2. Transplantation of barcoded EPO-exposed MPP2 confirmed their enrichment in myeloid-erythroid-biased clones. Collectively, our data show that EPO does act directly on MPP independent of the niche and modulates fate by remodeling the clonal composition of the MPP pool.

Hematopoiesis in numbers.

Hematopoiesis is a dynamic process in which stem and progenitor cells give rise to the ~1013 blood and immune cells distributed throughout the human body. We argue that a quantitative description of hematopoiesis can help consolidate existing data, identify knowledge gaps, and generate new hypotheses. Here, we review known numbers in murine and, where possible, human hematopoiesis, and consolidate murine numbers into a set of reference values. We present estimates of cell numbers, division and differentiation rates, cell size, and macromolecular composition for each hematopoietic cell type. We also propose guidelines to improve the reporting of measurements and highlight areas in which quantitative data are lacking. Overall, we show how quantitative approaches can be used to understand key properties of hematopoiesis.

In Vivo Tracking of Hematopoietic Stem and Progenitor Cell Ontogeny by Cellular Barcoding.

Cellular barcoding is a powerful technique that allows for high-throughput mapping of the fate of single cells, notably hematopoietic stem and progenitor cells (HSPCs) after transplantation. Unique artificial DNA fragments, termed barcodes, are stably inserted into HSPCs using lentiviral transduction, making sure that each individual cell receives a single unique barcode. Barcoded HSPCs are transplanted into sublethally irradiated mice where they reconstitute the hematopoietic system through proliferation and differentiation. During this process, the barcode of each HSPC is inherited by all of its daughter cells and their subsequent mature hematopoietic cell progeny. After sorting mature hematopoietic cell subsets, their barcodes can be retrieved from genomic DNA through nested PCR and sequencing. Analysis of barcode sequencing results allows for determination of clonal relationships between the mature cells, that is, which cell types were produced by a single barcoded HSPC, as well as the heterogeneity of the initial HSPC population. Here, we give a detailed protocol of a complete HSPC cellular barcoding experiment, starting with barcode lentivirus production, isolation, transduction, and transplantation of HSPCs, isolation of target cells followed by PCR amplification and sequencing of DNA barcodes. Finally, we describe the basic filtering and analysis steps of barcode sequencing data to ensure high-quality results.

HSPCs display within-family homogeneity in differentiation and proliferation despite population heterogeneity.

High-throughput single-cell methods have uncovered substantial heterogeneity in the pool of hematopoietic stem and progenitor cells (HSPCs), but how much instruction is inherited by offspring from their heterogeneous ancestors remains unanswered. Using a method that enables simultaneous determination of common ancestor, division number, and differentiation status of a large collection of single cells, our data revealed that murine cells that derived from a common ancestor had significant similarities in their division progression and differentiation outcomes. Although each family diversifies, the overall collection of cell types observed is composed of homogeneous families. Heterogeneity between families could be explained, in part, by differences in ancestral expression of cell surface markers. Our analyses demonstrate that fate decisions of cells are largely inherited from ancestor cells, indicating the importance of common ancestor effects. These results may have ramifications for bone marrow transplantation and leukemia, where substantial heterogeneity in HSPC behavior is observed.

Mouse multipotent progenitor 5 cells are located at the interphase between hematopoietic stem and progenitor cells.

Hematopoietic stem cells (HSCs) and distinct multipotent progenitor (MPP) populations (MPP1-4) contained within the Lin-Sca-1+c-Kit+ (LSK) compartment have previously been identified using diverse surface-marker panels. Here, we phenotypically define and functionally characterize MPP5 (LSK CD34+CD135-CD48-CD150-). Upon transplantation, MPP5 supports initial emergency myelopoiesis followed by stable contribution to the lymphoid lineage. MPP5, capable of generating MPP1-4 but not HSCs, represents a dynamic and versatile component of the MPP network. To characterize all hematopoietic stem and progenitor cells, we performed RNA-sequencing (RNA-seq) analysis to identify specific transcriptomic landscapes of HSCs and MPP1-5. This was complemented by single-cell RNA-seq analysis of LSK cells to establish the differentiation trajectories from HSCs to MPP1-5. In agreement with functional reconstitution activity, MPP5 is located immediately downstream of HSCs but upstream of the more committed MPP2-4. This study provides a comprehensive analysis of the LSK compartment, focusing on the functional and molecular characteristics of the newly defined MPP5 subset.

To portray clonal evolution in blood cancer, count your stem cells.

Clonal evolution, the process of expansion and diversification of mutated cells, plays an important role in cancer development, resistance, and relapse. Although clonal evolution is most often conceived of as driven by natural selection, recent studies uncovered that neutral evolution shapes clonal evolution in a significant proportion of solid cancers. In hematological malignancies, the interplay between neutral evolution and natural selection is also disputed. Because natural selection selects cells with a greater fitness, providing a growth advantage to some cells relative to others, the architecture of clonal evolution serves as indirect evidence to distinguish natural selection from neutral evolution and has been associated with different prognoses for the patient. Linear architecture, when the new mutant clone grows within the previous one, is characteristic of hematological malignancies and is typically interpreted as being driven by natural selection. Here, we discuss the role of natural selection and neutral evolution in the production of linear clonal architectures in hematological malignancies. Although it is tempting to attribute linear evolution to natural selection, we argue that a lower number of contributing stem cells accompanied by genetic drift can also result in a linear pattern of evolution, as illustrated by simulations of clonal evolution in hematopoietic stem cells. The number of stem cells contributing to long-term clonal evolution is not known in the pathological context, and we advocate that estimating these numbers in the context of cancer and aging is crucial to parsing out neutral evolution from natural selection, 2 processes that require different therapeutic strategies.

Comparing Phylogenetic Approaches to Reconstructing Cell Lineage From Microsatellites With Missing Data.

Due to the imperfect fidelity of DNA replication, somatic cells acquire DNA mutations at each division which record their lineage history. Microsatellites, tandem repeats of DNA nucleotide motifs, mutate more frequently than other genomic regions and by observing microsatellite lengths in single cells and implementing suitable inference procedures, the cell lineage tree of an organism can be reconstructed. Due to recent advances in single cell Next Generation Sequencing (NGS) and the phylogenetic methods used to infer lineage trees, this work investigates which computational approaches best exploit the lineage information found in single cell NGS data. We simulated trees representing cell division with mutating microsatellites, and tested a range of available phylogenetic algorithms to reconstruct cell lineage. We found that distance-based approaches are fast and accurate with fully observed data. However, Maximum Parsimony and the computationally intensive probabilistic methods are more robust to missing data and therefore better suited to reconstructing cell lineage from NGS datasets. We also investigated how robust reconstruction algorithms are to different tree topologies and mutation generation models. Our results show that the flexibility of Maximum Parsimony and the probabilistic approaches mean they can be adapted to allow good reconstruction across a range of biologically relevant scenarios.

A committed tissue-resident memory T cell precursor within the circulating CD8+ effector T cell pool.

An increasing body of evidence emphasizes the role of tissue-resident memory T cells (TRM) in the defense against recurring pathogens and malignant neoplasms. However, little is known with regard to the origin of these cells and their kinship to other CD8+ T cell compartments. To address this issue, we followed the antigen-specific progeny of individual naive CD8+ T cells to the T effector (TEFF), T circulating memory (TCIRCM), and TRM pools by lineage-tracing and single-cell transcriptome analysis. We demonstrate that a subset of T cell clones possesses a heightened capacity to form TRM, and that enriched expression of TRM-fate-associated genes is already apparent in the circulating TEFF offspring of such clones. In addition, we demonstrate that the capacity to generate TRM is permanently imprinted at the clonal level, before skin entry. Collectively, these data provide compelling evidence for early stage TRM fate decisions and the existence of committed TRM precursor cells in the circulatory TEFF compartment.

The immune system profoundly restricts intratumor genetic heterogeneity.

Tumors develop under the selective pressure of the immune system. However, it remains critical to establish how the immune system affects the clonal heterogeneity of tumors that often display cell-to-cell variation in genetic alterations and antigenic expression. To address these questions, we introduced a multicolor barcoding strategy to study the growth of a MYC-driven B cell lymphoma harboring a large degree of intratumor genetic diversity. Using intravital imaging, we visualized that lymphoma subclones grow as patches of sessile cells in the bone marrow, creating a spatially compartmentalized architecture for tumor diversity. Using multicolor barcoding and whole-exome sequencing, we demonstrated that immune responses strongly restrict intratumor genomic diversity and favor clonal dominance, a process mediated by the selective elimination of more immunogenic cells and amplified by epitope spreading. Anti-PD-1 treatment also narrowed intratumor diversity. Our results provide direct evidence that immune pressure shapes the level of intratumor genetic heterogeneity and have important implications for the design of therapeutic strategies.