Blood and immune development in human fetal bone marrow and Down syndrome

Abstract

Haematopoiesis in the bone marrow (BM) maintains blood and immune cell production throughout postnatal life. Haematopoiesis first emerges in human BM at 11-12 post conception weeks 1,2 , yet almost nothing is known about how fetal BM (FBM) evolves to meet the highly specialised needs of the fetus and newborn. Here, we detail the development of FBM, including stroma, using multi-omic assessment of mRNA and multiplexed protein epitope expression. We find that the full blood and immune cell repertoire is established in FBM in a short time window of 6-7 weeks early in the second trimester. FBM promotes rapid and extensive diversification of myeloid cells, with granulocytes, eosinophils and dendritic cell subsets emerging for the first time. Substantial B-lymphocyte expansion in FBM contrasts with FL at the same gestational age. Haematopoietic progenitors from FL, FBM and cord blood (CB) exhibit transcriptional and functional differences that contribute to tissue-specific identity and cellular diversification. Endothelial cell types form distinct vascular structures that we demonstrate are regionally compartmentalized within FBM. Finally, we reveal selective disruption of B-lymphocyte, erythroid and myeloid development due to cell-intrinsic differentiation bias as well as extrinsic regulation through an altered microenvironment in Down syndrome (trisomy 21).

CD116+ fetal precursors migrate to the perinatal lung and give rise to human alveolar macrophages

“…2 C and Table S1 ), a transcription factor that antagonizes MYB and represses macrophage self-renewal ( Aziz et al, 2009 ; Li et al, 2020 ; Soucie et al, 2016 ). Furthermore, fetal CD116 + CD64 − precursor-like cells expressed genes and transcription factors ( GATA1 , KLF1 , TAL1 ) associated with erythrocyte differentiation ( Popescu et al, 2019 ), consistent with preferential erythroid-myeloid hematopoiesis in human fetal liver ( Jardine et al, 2021 ). Therefore, fetal CD116 + CD64 − precursor-like cells resembled Myb -expressing erythro-myeloid progenitors (EMPs) and EMP-derived CD64 − myeloid progenitors that further differentiate into CD64 + fetal monocytes and alveolar macrophages in mice ( Gomez Perdiguero et al, 2015 ; Hoeffel et al, 2015 ; Li et al, 2020 ; Mass et al, 2016 ).…”

Single-cell transcriptomics reveals a distinct developmental state of KMT2A-rearranged infant B-cell acute lymphoblastic leukemia

“…In this context, a quantitative molecular assessment of hematopoietic cell states that does not rely on any individual marker, but instead builds on entire cellular transcriptomes, would provide an unbiased readout of cell states. Such high-resolution assessments are now feasible using single-cell mRNA sequencing to directly compare cancer cells to normal cells, including to fetal and adult hematopoietic cells [9][10][11][12] . We set out to study the developmental phenotype of KMT2A-rearranged infant B-ALL by comparing cancer cells with normal human hematopoietic cells.…”

Human bone marrow organoids for disease modelling, discovery and validation of therapeutic targets in hematological malignancies

“…4B). Canonical markers of bone marrow sinusoidal endothelium were more highly expressed in endothelial cells from VEGFA + C cultures compared to VEGFA alone, including FLT4 (VEGFR4), CD34 , MCAM , ANGPT2 , COL4A1 , COL4A2 , ITGA2 , CDC42EP1 and the notch ligand DLL4 (24,37,43,44), while DLK1 – a negative regulator of hematopoiesis (45) – was significantly downregulated in VEGFA + C-stimulated organoids (Figs. 4B & 4C).…”

“…To determine the transcriptional similarity of the bone marrow organoid cell types to native human hematopoietic tissues, the organoid scRNA-seq data was projected onto relevant human hematopoiesis single cell datasets of cells isolated from adult bone marrow (35,36), fetal liver and fetal bone marrow (37,38)using the Symphony package (39). This revealed extensive overlap of organoid-derived cells with HSPCs, myeloid subsets, fibroblast/MSC and endothelial cell types with the predicted cell types matching the cluster annotations (Fig.…”