Combined single-cell and spatial transcriptomics reveal the molecular, cellular and spatial bone marrow niche organization

Abstract

The bone marrow (BM) constitutes the primary site for life-long blood production and skeletal regeneration. However, its cellular composition and the spatial organization into distinct 'niches' remains controversial. Here, we combine single-cell and spatially resolved transcriptomics to systematically map the molecular and cellular composition of the endosteal, sinusoidal, and arteriolar BM niches. This allowed us to transcriptionally profile all major BM resident cell types, determine their localization, and clarify the cellular and spatial sources of key growth factors and cytokines. Our data demonstrate that previously unrecognized Cxcl12abundant reticular (CAR) cell subsets (i.e. Adipo-and Osteo-CAR cells) differentially localize to sinusoidal or arteriolar surfaces, locally act as 'professional cytokine secreting cells', and thereby establish distinct peri-vascular micro-niches. Importantly, we also demonstrate that the 3-dimensional organization of the BM can be accurately inferred from single-cell gene expression data using the newly developed RNA-Magnet algorithm. Together, our study reveals the cellular and spatial organization of BM niches, and offers a novel strategy to dissect the complex organization of whole organs in a systematic manner.One Sentence Summary: Integration of single-cell and spatial transcriptomics reveals the molecular, cellular and spatial organization of bone marrow niches

Deciphering cell–cell interactions and communication from gene expression

“…As this process is spatially coordinated, knowing the cellular localizations was crucial to understand, for example, interactions between XCR1 + dendritic cells and T cells with high expression of XCL1, which are important to recruit dendritic cells into the medulla of the thymus. Yet another study inferred the 3D organization of bone marrow — instead of using tissue imaging to map the cells — ultimately identifying signalling between immune and non-immune cells 53 . These examples show how cell localization can help elucidate interactions between spatially proximal regions.…”

“…2a ). Although several studies have used interactions between any class of cell-surface protein and secreted protein 32 , 53 , the predominant class of interactions used for studying CCC are known ligands and their cognate receptors.…”

“…Several high-quality lists of ligand–receptor pairs exist for model organisms 7 , 14 – 16 , 22 , 29 , 30 , 32 , 33 , 38 , 53 – 55 , 67 , 84 . However, studying cell–cell communication in organisms with fewer protein–protein interaction (PPI) data requires additional effort, especially in imputing ligand–receptor pairs through heuristic approaches and subsequent manual curation to increase the confidence in the list.…”

Osteoclast Fusion: Physiological Regulation of Multinucleation through Heterogeneity—Potential Implications for Drug Sensitivity

“…For more information on this issue, please refer to a recent review [ 9 ]. Macrophage-colony stimulating factor (M-CSF) is also found to be mostly expressed at the bone surface, but also along vascular structures in the marrow cavity [ 25 , 26 , 27 ]. This heterogenic distribution of osteoclast precursors exposed to M-CSF and RANKL, with variations in time and space, is likely to create a variety of pre-osteoclasts that express different molecular factors.…”

Integrative Analysis of Spatial and Single-Cell Transcriptomics Reveals Principles of Tissue Organization and Intercellular Communication in Mouse Olfactory Bulb

“…Identifying the communicating pairs of cell-types and their communication mechanisms (in terms of receptors and ligands) is currently a major focus of scRNA-seq studies. Recent studies suggest that the communications between certain cell-types may be enriched within specific parts of a tissue (commonly termed microenvironments or niches 34,36 ). This concept of spatially localized GRNs has been noted in the literature 44 .…”