Simultaneous Assessment of Kinship, Division Number, and Phenotype <em>via</em> 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 ...

Institut Curie

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.

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

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.

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

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.

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

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 summary, CellDestiny is an easy-to-use and versatile toolkit that enables biologists to visualize and analyze single-cell lineage tracing data.

Tamar Tak

Quantitative Immuno-hematology,
CNRS UMR168,
Quantitative Immuno-hematology, CNRS UMR168

Institut Curie

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

Tamar Tak

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Institut Curie

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

Quantitative Immuno-hematology,
CNRS UMR168,
Quantitative Immuno-hematology, CNRS UMR168