Biology subjects

Dahlin, J. S.

Publications and source records attributed to Dahlin, J. S..

3 recordsLinked to original sources

bioRxiv2026

Modelling human haematopoietic stem cell commitment ex vivo identifies IL-33 as a regulator of megakaryopoiesis

Commitment events to specific blood lineages arise from single hematopoietic stem cells (HSCs) and are influenced by stress, inflammation and disease. However, the understanding of how such events are regulated in human haematopoiesis is limited by the lack of tractable in vitro models. In this study, we introduce a novel Early Progenitor Differentiation (EPD) assay to study the initial lineage commitment of human 49+ HSCs, in a system faithfully recapitulating cell states observed in vivo. Combining single cell -omics approaches and single cell functional assays, we show that IL-33 acts directly on human 49f+ HSCs activating the MAPK pathway to enhance their commitment towards Megakaryocytic-Erythroid-Mast cell Progenitors and subsequently megakaryopoiesis. This occurs without affecting HSC self-renewal via accelerated establishment of chromatin programmes associated with Erythroid and Megakaryocyte and mast cells lineages. Our findings demonstrate the utility of the EPD model to identify molecular regulators of human HSC differentiation and uncover a new role of IL-33 in haematopoiesis.

cell biology↗

bioRxiv2018

Single-cell analysis reveals the KIT D816V mutation in hematopoietic stem and progenitor cells in systemic mastocytosis

Background: Systemic mastocytosis (SM) is a hematological disease characterized by organ infiltration by neoplastic mast cells. Almost all SM patients have a mutation in the gene encoding the tyrosine kinase receptor KIT causing a D816V substitution and autoactivation of the receptor. Mast cells and CD34+ hematopoietic progenitors can carry the mutation, however, in which progenitor cell subset the mutation arises is unknown. We aimed to investigate the distribution of the D816V mutation in single mast cells and single hematopoietic stem and progenitor cells. Methods: Fluorescence-activated single-cell index sorting and D816V mutation assessment were applied to analyze mast cells and more than 10,000 CD34+ bone marrow progenitors across 10 hematopoietic progenitor subsets. In vitro assays verified cell-forming potential. Findings: We found that in SM 60-99% of the mast cells harbored the D816V mutation. Despite increased frequencies of mast cells in SM patients compared with control subjects, the hematopoietic progenitor subset frequencies were comparable. Nevertheless, the mutation could be detected throughout the hematopoietic landscape of SM patients, from hematopoietic stem cells to more lineage-primed progenitors. In addition, we demonstrate that Fc{varepsilon}RI+ bone marrow progenitors exhibit mast cell-forming potential, and we describe aberrant CD45RA expression on SM mast cells for the first time. Interpretation: The KIT D816V mutation arises in early hematopoietic stem and progenitor cells and the mutation frequency is approaching 100% in mature mast cells, which express the aberrant marker CD45RA.

immunology↗

bioRxiv2017

Graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells

Single-cell RNA-seq quantifies biological heterogeneity across both discrete cell types and continuous cell transitions. Partition-based graph abstraction (PAGA) provides an interpretable graph-like map of the arising data manifold, based on estimating connectivity of manifold partitions (https://github.com/theislab/paga). PAGA maps provide interpretable discrete and continuous latent coordinates for both disconnected and continuous structure in data, preserve the global topology of data, allow analyzing data at different resolutions and result in much higher computational efficiency of the typical exploratory data analysis workflow -- one million cells take on the order of a minute, a speedup of 130 times compared to UMAP. We demonstrate the method by inferring structure-rich cell maps with consistent topology across four hematopoietic datasets, confirm the reconstruction of lineage relations of adult planaria and the zebrafish embryo, benchmark computational performance on a neuronal dataset and detect a biological trajectory in one deep-learning processed image dataset.

bioinformatics↗