Nikolaos Barkas

Single-cell transcriptomics uncovers distinct molecular signatures of stem cells in chronic myeloid leukemia

Recent advances in single-cell transcriptomics are ideally placed to unravel intratumoral heterogeneity and selective resistance of cancer stem cell (SC) subpopulations to molecularly targeted cancer therapies. However, current single-cell RNA-sequencing approaches lack the sensitivity required to reliably detect somatic mutations. We developed a method that combines high-sensitivity mutation detection with whole-transcriptome analysis of the same single cell. We applied this technique to analyze more than 2,000 SCs from patients with chronic myeloid leukemia (CML) throughout the disease course, revealing heterogeneity of CML-SCs, including the identification of a subgroup of CML-SCs with a distinct molecular signature that selectively persisted during prolonged therapy. Analysis of nonleukemic SCs from patients with CML also provided new insights into cell-extrinsic disruption of hematopoiesis in CML associated with clinical outcome. Furthermore, we used this single-cell approach to identify a blast-crisis-specific SC population, which was also present in a subclone of CML-SCs during the chronic phase in a patient who subsequently developed blast crisis. This approach, which might be broadly applied to any malignancy, illustrates how single-cell analysis can identify subpopulations of therapy-resistant SCs that are not apparent through cell-population analysis.

Single-cell profiling of human megakaryocyte-erythroid progenitors identifies distinct megakaryocyte and erythroid differentiation pathways

BackgroundRecent advances in single-cell techniques have provided the opportunity to finely dissect cellular heterogeneity within populations previously defined by “bulk” assays and to uncover rare cell types. In human hematopoiesis, megakaryocytes and erythroid cells differentiate from a shared precursor, the megakaryocyte-erythroid progenitor (MEP), which remains poorly defined.ResultsTo clarify the cellular pathway in erythro-megakaryocyte differentiation, we correlate the surface immunophenotype, transcriptional profile, and differentiation potential of individual MEP cells. Highly purified, single MEP cells were analyzed using index fluorescence-activated cell sorting and parallel targeted transcriptional profiling of the same cells was performed using a specifically designed panel of genes. Differentiation potential was tested in novel, single-cell differentiation assays. Our results demonstrate that immunophenotypic MEP comprise three distinct subpopulations: “Pre-MEP,” enriched for erythroid/megakaryocyte progenitors but with residual myeloid differentiation capacity; “E-MEP,” strongly biased towards erythroid differentiation; and “MK-MEP,” a previously undescribed, rare population of cells that are bipotent but primarily generate megakaryocytic progeny. Therefore, conventionally defined MEP are a mixed population, as a minority give rise to mixed-lineage colonies while the majority of cells are transcriptionally primed to generate exclusively single-lineage output.ConclusionsOur study clarifies the cellular hierarchy in human megakaryocyte/erythroid lineage commitment and highlights the importance of using a combination of single-cell approaches to dissect cellular heterogeneity and identify rare cell types within a population. We present a novel immunophenotyping strategy that enables the prospective identification of specific intermediate progenitor populations in erythro-megakaryopoiesis, allowing for in-depth study of disorders including inherited cytopenias, myeloproliferative disorders, and erythromegakaryocytic leukemias.

Genome-wide and parental allele-specific analysis of CTCF and cohesin DNA binding in mouse brain reveals a tissue-specific binding pattern and an association with imprinted differentially methylated regions

DNA binding factors are essential for regulating gene expression. CTCF and cohesin are DNA binding factors with central roles in chromatin organization and gene expression. We determined the sites of CTCF and cohesin binding to DNA in mouse brain, genome wide and in an allele-specific manner with high read-depth ChIP-seq. By comparing our results with existing data for mouse liver and embryonic stem (ES) cells, we investigated the tissue specificity of CTCF binding sites. ES cells have fewer unique CTCF binding sites occupied than liver and brain, consistent with a ground-state pattern of CTCF binding that is elaborated during differentiation. CTCF binding sites without the canonical consensus motif were highly tissue specific. In brain, a third of CTCF and cohesin binding sites coincide, consistent with the potential for many interactions between cohesin and CTCF but also many instances of independent action. In the context of genomic imprinting, CTCF and/or cohesin bind to a majority but not all differentially methylated regions, with preferential binding to the unmethylated parental allele. Whether the parental allele-specific methylation was established in the parental germlines or post-fertilization in the embryo is not a determinant in CTCF or cohesin binding. These findings link CTCF and cohesin with the control regions of a subset of imprinted genes, supporting the notion that imprinting control is mechanistically diverse.

Niche-mediated depletion of the normal hematopoietic stem cell reservoir by Flt3-ITD-induced myeloproliferation.

Although previous studies suggested that the expression of FMS-like tyrosine kinase 3 (Flt3) initiates downstream of mouse hematopoietic stem cells (HSCs), FLT3 internal tandem duplications (FLT3 ITDs) have recently been suggested to intrinsically suppress HSCs. Herein, single-cell interrogation found Flt3 mRNA expression to be absent in the large majority of phenotypic HSCs, with a strong negative correlation between Flt3 and HSC-associated gene expression. Flt3-ITD knock-in mice showed reduced numbers of phenotypic HSCs, with an even more severe loss of long-term repopulating HSCs, likely reflecting the presence of non-HSCs within the phenotypic HSC compartment. Competitive transplantation experiments established that Flt3-ITD compromises HSCs through an extrinsically mediated mechanism of disrupting HSC-supporting bone marrow stromal cells, with reduced numbers of endothelial and mesenchymal stromal cells showing increased inflammation-associated gene expression. Tumor necrosis factor (TNF), a cell-extrinsic potent negative regulator of HSCs, was overexpressed in bone marrow niche cells from FLT3-ITD mice, and anti-TNF treatment partially rescued the HSC phenotype. These findings, which establish that Flt3-ITD–driven myeloproliferation results in cell-extrinsic suppression of the normal HSC reservoir, are of relevance for several aspects of acute myeloid leukemia biology.

Linking transcriptional and genetic tumor heterogeneity through allele analysis of single-cell RNA-seq data

Characterization of intratumoral heterogeneity is critical to cancer therapy, as the presence of phenotypically diverse cell populations commonly fuels relapse and resistance to treatment. Although genetic variation is a well-studied source of intratumoral heterogeneity, the functional impact of most genetic alterations remains unclear. Even less understood is the relative importance of other factors influencing heterogeneity, such as epigenetic state or tumor microenvironment. To investigate the relationship between genetic and transcriptional heterogeneity in a context of cancer progression, we devised a computational approach called HoneyBADGER to identify copy number variation and loss of heterozygosity in individual cells from single-cell RNA-sequencing data. By integrating allele and normalized expression information, HoneyBADGER is able to identify and infer the presence of subclone-specific alterations in individual cells and reconstruct the underlying subclonal architecture. By examining several tumor types, we show that HoneyBADGER is effective at identifying deletions, amplifications, and copy-neutral loss-of-heterozygosity events and is capable of robustly identifying subclonal focal alterations as small as 10 megabases. We further apply HoneyBADGER to analyze single cells from a progressive multiple myeloma patient to identify major genetic subclones that exhibit distinct transcriptional signatures relevant to cancer progression. Other prominent transcriptional subpopulations within these tumors did not line up with the genetic subclonal structure and were likely driven by alternative, nonclonal mechanisms. These results highlight the need for integrative analysis to understand the molecular and phenotypic heterogeneity in cancer.

Perivascular Niche Cells Sense Thrombocytopenia and Activate Platelet-Biased Hscs in an IL-1 Dependent Manner

Hematopoietic stem cells (HSC) are responsible for the on demand production of blood cells both in homeostasis and in response to stress. HSCs reside in specialized niches bone marrow (BM) niches, which regulate their function. These niches are dynamic entities with the capacity to sense and respond to specific requirements in blood production, but the mechanisms underlying this dynamic regulation remain unclear. Accumulating evidence indicate that HSCs are highly heterogeneous, and different BM niches have been proposed, potentially supporting different HSC subsets. We recently identified a subset of HSCs, which is molecularly and functionally primed for platelet replenishment. However, the role of the niche in the regulation of platelet-biased HSC function is still unknown. This work aims at investigating the role of the BM niche in the response of platelet-biased HSCs to thrombocytopenia. In response to platelet depletion platelet-biased HSCs are rapidly and selectively recruited into cell cycle, through a feedback mechanism to replenish platelet numbers and homeostasis. Using RNA-sequencing to analyze different BM niche cell populations and HSC subsets we identified IL-1 as a cytokine released upon platelet depletion and specifically sensed by niche LepR+ perivascular cells. Abrogation of IL-1 signaling specifically in LepR+ niche cells but not in hematopoietic cells impaired the platelet-biased HSC response to platelet depletion. This process was found to be dependent on platelet activation. This work uncovers a molecular mechanism involving the pro-inflammatory signal IL-1 and the niche perivascular cell compartment in the rapid activation of platelet biased HSCs to thrombocytopenia, highlighting a mechanism by which a distinct HSC subset senses and responds to the loss of the lineage it is intrinsically primed for.