Multi-layered Spatial Transcriptomics Identify Secretory Factors Promoting Human Hematopoietic Stem Cell Development

Abstract

Summary Hematopoietic stem cells (HSCs) first emerge in the embryonic aorta-gonad-mesonephros (AGM) region. Studies of model organisms defined intersecting signaling pathways that converge to promote HSC emergence predominantly in the ventral domain of the dorsal aorta. Much less is known about mechanisms driving HSC development in humans. Here, to identify secreted signals underlying human HSC development, we combined spatial transcriptomics analysis of dorsoventral polarized signaling in the aorta with gene expression profiling of sorted cell populations and single cells. Our analysis revealed a subset of aortic endothelial cells with a downregulated arterial signature and a predicted lineage relationship with the emerging HSC/progenitor population. Analysis of the ventrally polarized molecular landscape identified endothelin 1 as an important secreted regulator of human HSC development. The obtained gene expression datasets will inform future studies on mechanisms of HSC development in vivo and on generation of clinically relevant HSCs in vitro .

Modulation of APLNR Signaling Is Required during the Development and Maintenance of the Hematopoietic System

“…We noted that a proportion of Aplnr -tdTomato-positive cells also expressed hematopoietic markers implying that it is expressed at the EHT transition stage. This is in keeping with single-cell sequencing analyses of human AGM implying that APLNR was expressed in hemogenic endothelium ( Crosse et al., 2020 ). Two further studies have reported the downregulation of Aplnr as endothelial cells acquire hematopoietic markers during EHT ( Bruveris et al., 2020 ; Oatley et al., 2020 ).…”

“…The Apelin receptor gene ( Aplnr/Agtrl1/Apj ) encodes a member of the G protein-coupled receptor family and has been implicated in cardiac, endothelial, and hematopoietic development in a number of model systems ( D'Aniello et al., 2009 ; Inui et al., 2006 ; Quertermous, 2007 ; Scott et al., 2007 ). Pertinent to this study is the involvement of Aplnr Aplnr in endothelial cell maturation during development and the fact that it appears to be expressed at a higher level in endothelial cells of the AGM region, implying that it could be related to their hemogenic potential both in mouse ( Kidoya et al., 2015 ; Kidoya et al., 2008 , 2010 ) and human embryos ( Crosse et al., 2020 ). In the adult bone marrow, endothelial cells that express APELIN, one of the APLNR ligands, participate in vascular remodeling after irradiation and drive post-transplant recovery through feedback from HSPCs ( Chen et al., 2019 ).…”

“…These data support the hypothesis that the APLNR signaling pathway is active during the emergence of HSCs in vivo . To further define which cell types within the AGM express the genes encoding APLNR and its ligands we analyzed published datasets from single-cell RNA sequencing of mouse AGM tissue (GEO: GSE143637 ) ( Vink et al., 2020 ), human AGM tissue (GEO: GSE151877 ; sample GSM4592621) ( Crosse et al., 2020 ) and differentiating human iPSCs (Database: EMBL EBI Arrayexpress; E-MTAB-9295 ( Fidanza et al., 2020 ). Aplnr/APLNR is expressed at a relatively high level in most of the cells associated with endothelial cell clusters in both mouse and human AGM and in differentiating human iPSCs ( Figures 5 B–5D).…”

“…Specifically, the Aplnr expression profile in FACS-sorted CD31 + cKIT hi GATA2 med cells isolated from the AGM region of E11 embryos was generated using the online browser ( https://gottgens-lab.stemcells.cam.ac.uk/DZIERZAK/ ) (GEO: GSE143637 ) ( Vink et al., 2020 ). The APLNR expression profile in sorted CD34+ cells from the dissected AGM ventral region from CS16 human embryos was analyzed from a GEO downloaded dataset (GEO: GSE1518767 ; sample GSM4592621) ( Crosse et al., 2020 ). Data were analyzed using the R package Seurat 3.2.2, following the standard pipeline ( https://www.cell.com/cell/fulltext/S0092-8674(19)30559-8 ).…”

“…Accession numbers for the published RNA sequencing datasets that were analyzed in this study include GEO: GSE143637 ( Vink et al., 2020 ), GEO: GSE1518767 ; sample GSM4592621 ( Crosse et al., 2020 ), and EMBL EBI Arrayexpress: E-MTAB-9295 ( Fidanza et al., 2020 ).…”