Single-cell analysis reveals dynamic changes of neural cells in developing human spinal cord
TL;DR: This paper performed single-cell RNA sequencing of human spinal cord cells during embryonic and fetal stages that cover neuron generation as well as astrocytes and oligodendrocyte differentiation.
Abstract: During central nervous system development, neurogenesis and gliogenesis occur in an orderly manner to create precise neural circuitry. However, no systematic dataset of neural lineage development that covers both neurogenesis and gliogenesis for the human spinal cord is available. We here perform single-cell RNA sequencing of human spinal cord cells during embryonic and fetal stages that cover neuron generation as well as astrocytes and oligodendrocyte differentiation. We also map the timeline of sensory neurogenesis and gliogenesis in the spinal cord. We further identify a group of EGFR-expressing transitional glial cells with radial morphology at the onset of gliogenesis, which progressively acquires differentiated glial cell characteristics. These EGFR-expressing transitional glial cells exhibited a unique position-specific feature during spinal cord development. Cell crosstalk analysis using CellPhoneDB indicated that EGFR glial cells can persistently interact with other neural cells during development through Delta-Notch and EGFR signaling. Together, our results reveal stage-specific profiles and dynamics of neural cells during human spinal cord development.
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TL;DR: A cellular taxonomy of the adult human spinal cord using single-nucleus RNA sequencing with spatial transcriptomics and antibody validation is presented in this article , which identifies 29 glial clusters and 35 neuronal clusters, organized principally by anatomical location.
17 citations
28 Mar 2022
TL;DR: In this article , a cellular taxonomy of the adult human spinal cord using single nucleus RNA-sequencing with spatial transcriptomics and antibody validation was presented, including 29 glial clusters, including rare cell types such as ependymal cells, and 35 neuronal clusters, which were organized principally by anatomical location.
Abstract: Abstract The mammalian spinal cord functions as a community of glial and neuronal cell types to accomplish sensory processing, autonomic control, and movement; conversely, the dysfunction of these cell types following spinal cord injury or disease states can lead to chronic pain, paralysis, and death. While we have made great strides in understanding spinal cellular diversity in animal models, it is crucial to characterize human biology directly to uncover specialized features of basic function and to illuminate human pathology. Here, we present a cellular taxonomy of the adult human spinal cord using single nucleus RNA-sequencing with spatial transcriptomics and antibody validation. We observed 29 glial clusters, including rare cell types such as ependymal cells, and 35 neuronal clusters, which we found are organized principally by anatomical location. To demonstrate the potential of this resource for understanding human disease, we analyzed the transcriptome of spinal motoneurons that are prone to degeneration in amyotrophic lateral sclerosis (ALS) and other diseases. We found that, compared with all other spinal neurons, human motoneurons are defined by genes related to cell size, cytoskeletal structure, and ALS, thereby supporting a model of a specialized motoneuron molecular repertoire that underlies their selective vulnerability to disease. We include a publicly available browsable web resource with this work, in the hope that it will catalyze future discoveries about human spinal cord biology.
7 citations
TL;DR: This Spotlight discusses key insights from single-cell RNA-sequencing studies in mammals, and proposes future directions to fill the remaining gaps, and necessary complementary techniques to create an atlas integrated in space and time of human brain development.
Abstract: Understanding human brain development is of fundamental interest but is also very challenging. Single-cell RNA-sequencing studies in mammals have revealed that brain development is a highly dynamic process with tremendous, previously concealed, cellular heterogeneity. This Spotlight discusses key insights from these studies and their implications for experimental models. We survey published single-cell RNA-sequencing studies of mouse and human brain development, organized by anatomical regions and developmental time points. We highlight remaining gaps in the field, predominantly concerning human brain development. We propose future directions to fill the remaining gaps, and necessary complementary techniques to create an atlas integrated in space and time of human brain development.
6 citations
TL;DR: Zhang et al. as mentioned in this paper compared the transcriptomes of human fetal brain-derived NSPCs, spinal cord-derived neural stem progenitor cells (SCNSPCs) and H9 embryonic stem-cell derived NSPC (H9-NSPC) in vitro and subsequently transplanted each cell type on a collagen scaffold into a T8-9 complete SCI rat model in vivo.
4 citations
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References
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TL;DR: Notch signaling defines an evolutionarily ancient cell interaction mechanism, which plays a fundamental role in metazoan development, providing a general developmental tool to influence organ formation and morphogenesis.
Abstract: Notch signaling defines an evolutionarily ancient cell interaction mechanism, which plays a fundamental role in metazoan development. Signals exchanged between neighboring cells through the Notch receptor can amplify and consolidate molecular differences, which eventually dictate cell fates. Thus, Notch signals control how cells respond to intrinsic or extrinsic developmental cues that are necessary to unfold specific developmental programs. Notch activity affects the implementation of differentiation, proliferation, and apoptotic programs, providing a general developmental tool to influence organ formation and morphogenesis.
5,834 citations
TL;DR: A cell atlas of mouse organogenesis provides a global view of developmental processes occurring during this critical period, including focused analyses of the apical ectodermal ridge, limb mesenchyme and skeletal muscle.
Abstract: Mammalian organogenesis is a remarkable process. Within a short timeframe, the cells of the three germ layers transform into an embryo that includes most of the major internal and external organs. Here we investigate the transcriptional dynamics of mouse organogenesis at single-cell resolution. Using single-cell combinatorial indexing, we profiled the transcriptomes of around 2 million cells derived from 61 embryos staged between 9.5 and 13.5 days of gestation, in a single experiment. The resulting ‘mouse organogenesis cell atlas’ (MOCA) provides a global view of developmental processes during this critical window. We use Monocle 3 to identify hundreds of cell types and 56 trajectories, many of which are detected only because of the depth of cellular coverage, and collectively define thousands of corresponding marker genes. We explore the dynamics of gene expression within cell types and trajectories over time, including focused analyses of the apical ectodermal ridge, limb mesenchyme and skeletal muscle. Data from single-cell combinatorial-indexing RNA-sequencing analysis of 2 million cells from mouse embryos between embryonic days 9.5 and 13.5 are compiled in a cell atlas of mouse organogenesis, which provides a global view of developmental processes occurring during this critical period.
1,865 citations
TL;DR: The structure and content of CellPhoneDB is outlined, procedures for inferring cell–cell communication networks from single-cell RNA sequencing data are provided and a practical step-by-step guide to help implement the protocol is presented.
Abstract: Cell–cell communication mediated by ligand–receptor complexes is critical to coordinating diverse biological processes, such as development, differentiation and inflammation. To investigate how the context-dependent crosstalk of different cell types enables physiological processes to proceed, we developed CellPhoneDB, a novel repository of ligands, receptors and their interactions. In contrast to other repositories, our database takes into account the subunit architecture of both ligands and receptors, representing heteromeric complexes accurately. We integrated our resource with a statistical framework that predicts enriched cellular interactions between two cell types from single-cell transcriptomics data. Here, we outline the structure and content of our repository, provide procedures for inferring cell–cell communication networks from single-cell RNA sequencing data and present a practical step-by-step guide to help implement the protocol. CellPhoneDB v.2.0 is an updated version of our resource that incorporates additional functionalities to enable users to introduce new interacting molecules and reduces the time and resources needed to interrogate large datasets. CellPhoneDB v.2.0 is publicly available, both as code and as a user-friendly web interface; it can be used by both experts and researchers with little experience in computational genomics. In our protocol, we demonstrate how to evaluate meaningful biological interactions with CellPhoneDB v.2.0 using published datasets. This protocol typically takes ~2 h to complete, from installation to statistical analysis and visualization, for a dataset of ~10 GB, 10,000 cells and 19 cell types, and using five threads. CellPhoneDB combines an interactive database and a statistical framework for the exploration of ligand–receptor interactions inferred from single-cell transcriptomics measurements.
1,392 citations
TL;DR: It is shown here that constitutive expression of SOX2 inhibits neuronal differentiation and results in the maintenance of progenitor characteristics, and that SOXB1 signaling is both necessary and sufficient to maintain panneural properties of neural progenitors.
1,280 citations
TL;DR: RNA-sequencing analysis of cells in the human cortex enabled identification of diverse cell types, revealing well-conserved architecture and homologous cell types as well as extensive differences when compared with datasets covering the analogous region of the mouse brain.
Abstract: Elucidating the cellular architecture of the human cerebral cortex is central to understanding our cognitive abilities and susceptibility to disease. Here we used single-nucleus RNA-sequencing analysis to perform a comprehensive study of cell types in the middle temporal gyrus of human cortex. We identified a highly diverse set of excitatory and inhibitory neuron types that are mostly sparse, with excitatory types being less layer-restricted than expected. Comparison to similar mouse cortex single-cell RNA-sequencing datasets revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of properties of human cell types. Despite this general conservation, we also found extensive differences between homologous human and mouse cell types, including marked alterations in proportions, laminar distributions, gene expression and morphology. These species-specific features emphasize the importance of directly studying human brain.
1,044 citations