Regulation of human lung alveolar multipotent cells by a novel p38α MAPK/miR-17-92 axis

The cellular and molecular mechanisms that control lung homeostasis and regeneration are still poorly understood. It has been proposed that a population of cells exists in the mouse lung with the potential to differentiate into all major lung bronchioalveolar epithelium cell types in homeostasis or in response to virus infection. A new population of E-Cad/Lgr6(+) putative stem cells has been isolated, and indefinitely expanded from human lungs, harbouring both, self-renewal capacity and the potency to differentiate in vitro and in vivo. Recently, a putative population of human lung stem cells has been proposed as being c-Kit(+). Unlike Integrin-α6(+) or c-Kit(+) cells, E-Cad/Lgr6(+) single-cell injections in the kidney capsule produce differentiated bronchioalveolar tissue, while retaining self-renewal, as they can undergo serial transplantations under the kidney capsule or in the lung. In addition, a signalling network involving the p38α pathway, the activation of p53 and the regulation of the miR-17-92 cluster has been identified. Disruption of the proper cross-regulation of this signalling axis might be involved in the promotion of human lung diseases.     

Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE

The ability to analyze multiple single-cell parameters is critical for understanding cellular heterogeneity. Despite recent advances in measurement technology, methods for analyzing high-dimensional single-cell data are often subjective, labor intensive and require prior knowledge of the biological system. To objectively uncover cellular heterogeneity from single-cell measurements, we present a versatile computational approach, spanning-tree progression analysis of density-normalized events (SPADE). We applied SPADE to flow cytometry data of mouse bone marrow and to mass cytometry data of human bone marrow. In both cases, SPADE organized cells in a hierarchy of related phenotypes that partially recapitulated well-described patterns of hematopoiesis. We demonstrate that SPADE is robust to measurement noise and to the choice of cellular markers. SPADE facilitates the analysis of cellular heterogeneity, the identification of cell types and comparison of functional markers in response to perturbations.     

Human SERPINB12 Is an Abundant Intracellular Serpin Expressed in Most Surface and Glandular Epithelia

The intracellular serine protease inhibitors (serpins) are an important family of proteins that protect cells form proteinase-mediated injury. Understanding the tissue and cellular expression pattern of this protein family can provide important insights into their physiologic roles. For example, high expression in epithelial tissues, such as lung, may suggest a biologic function in cellular defense, secretion, or selective absorption. Although the expression pattern of many of the intracellular serpins has been well described, one member of this class, SERPINB12, has not been carefully examined. We generated a mouse monoclonal antibody directed against human SERPINB12 and delineated its specificity and tissue and cell type distribution pattern through immunoblotting and immunohistochemistry, respectively. This monoclonal antibody was human specific and did not cross-react with other human intracellular serpins or mouse Serpinb12. SERPINB12 was found in nearly all the tissues investigated. In addition, this serpin was found in multiple cell types within individual tissues but primarily the epithelium. These data suggest that SERPINB12, like some other intracellular serpins, may play a vital role in barrier function by providing protection of epithelial cells.     

De novo spatiotemporal modelling of cell-type signatures in the developmental human heart using graph convolutional neural networks

With the emergence of high throughput single cell techniques, the understanding of the molecular and cellular diversity of mammalian organs have rapidly increased. In order to understand the spatial organization of this diversity, single cell data is often integrated with spatial data to create probabilistic cell maps. However, targeted cell typing approaches relying on existing single cell data achieve incomplete and biased maps that could mask the true diversity present in a tissue slide. Here we applied a de novo technique to spatially resolve and characterize cellular diversity of in situ sequencing data during human heart development. We obtained and made accessible well defined spatial cell-type maps of fetal hearts from 4.5 to 9 post conception weeks, not biased by probabilistic cell typing approaches. With our analysis, we could characterize previously unreported molecular diversity within cardiomyocytes and epicardial cells and identified their characteristic expression signatures, comparing them with specific subpopulations found in single cell RNA sequencing datasets. We further characterized the differentiation trajectories of epicardial cells, identifying a clear spatial component on it. All in all, our study provides a novel technique for conducting de novo spatial-temporal analyses in developmental tissue samples and a useful resource for online exploration of cell-type differentiation during heart development at sub-cellular image resolution.     

Identifying Cell Types from Spatially Referenced Single-Cell Expression Datasets

Complex tissues, such as the brain, are composed of multiple different cell types, each of which have distinct and important roles, for example in neural function. Moreover, it has recently been appreciated that the cells that make up these sub-cell types themselves harbour significant cell-to-cell heterogeneity, in particular at the level of gene expression. The ability to study this heterogeneity has been revolutionised by advances in experimental technology, such as Wholemount in Situ Hybridizations (WiSH) and single-cell RNA-sequencing. Consequently, it is now possible to study gene expression levels in thousands of cells from the same tissue type. After generating such data one of the key goals is to cluster the cells into groups that correspond to both known and putatively novel cell types. Whilst many clustering algorithms exist, they are typically unable to incorporate information about the spatial dependence between cells within the tissue under study. When such information exists it provides important insights that should be directly included in the clustering scheme. To this end we have developed a clustering method that uses a Hidden Markov Random Field (HMRF) model to exploit both quantitative measures of expression and spatial information. To accurately reflect the underlying biology, we extend current HMRF approaches by allowing the degree of spatial coherency to differ between clusters. We demonstrate the utility of our method using simulated data before applying it to cluster single cell gene expression data generated by applying WiSH to study expression patterns in the brain of the marine annelid Platynereis dumereilii. Our approach allows known cell types to be identified as well as revealing new, previously unexplored cell types within the brain of this important model system.     

Single-cell RNA sequencing analysis to characterize cells and gene expression landscapes in atrial septal defect

This study aimed to characterize the cells and gene expression landscape in atrial septal defect (ASD). We performed single-cell RNA sequencing of cells derived from cardiac tissue of an ASD patient. Unsupervised clustering analysis was performed to identify different cell populations, followed by the investigation of the cellular crosstalk by analysing ligand-receptor interactions across cell types. Finally, differences between ASD and normal samples for all cell types were further investigated. An expression matrix of 18,411 genes in 6487 cells was obtained and used in this analysis. Five cell types, including cardiomyocytes, endothelial cells, smooth muscle cells, fibroblasts and macrophages were identified. ASD showed a decreased proportion of cardiomyocytes and an increased proportion of fibroblasts. There was more cellular crosstalk among cardiomyocytes, fibroblasts and macrophages, especially between fibroblast and macrophage. For all cell types, the majority of the DEGs were downregulated in ASD samples. For cardiomyocytes, there were 199 DEGs (42 upregulated and 157 downregulated) between ASD and normal samples. PPI analysis showed that cardiomyocyte marker gene FABP4 interacted with FOS, while FOS showed interaction with NPPA. Cell trajectory analysis showed that FABP4, FOS, and NPPA showed different expression changes along the pseudotime trajectory. Our results showed that single-cell RNA sequencing provides a powerful tool to study DEG profiles in the cell subpopulations of interest at the single-cell level. These findings enhance the understanding of the underlying mechanisms of ASD at both the cellular and molecular level and highlight potential targets for the treatment of ASD.     

Effects of local tissue environment on the differentiation of neural crest cells in turtle, with special reference to understanding the spatial distribution of pigment cells

The spatial distribution of neural crest-derived pigment cells in turtles differs markedly from those found in chickens and mice. One hypothesis to explain such differences in the spatial distribution of pigment cells is that local tissue factors interact with neural crest cells, thereby determining their differentiation into pigment-synthesizing cells. It is reported here that local tissue factors in the soft-shell turtle (Trionyx sinensis japonicus) play a critical role in the development of melanophores from neural crest cells during embryogenesis. Undifferentiated neural crest cells derived from trunk neural tubes were co-cultured in vitro with homochronous somites, or with heterochronous dermis, lung or liver for 14 days. Melanophore differentiation from neural crest cells was significantly promoted when co-cultured with cells from lung, somites or dermis, but not when co-cultured with liver cells. These results suggest that local tissue factors stimulate the differentiation of pluripotent neural crest derivatives toward pigment cells. It is proposed that specific environmental cues play an important role in the spatial distribution of pigment cells in a variety of vertebrate species.     

Cell type diversity in scallop adductor muscles revealed by single-cell RNA-Seq

Studies on cell atlas in marine invertebrates provide a better understanding of cell types, stem cell maintenance, and lineages of cell differentiation. To investigate the molecular features of various cell types in molluscan muscles, we performed single-cell RNA sequencing (scRNA-seq) to map cell types in scallop adductor muscles. We uncovered the cell type-specific features of 20 cell clusters defined by the expression of multiple specific molecular markers. These cell clusters are mainly classified into four broad classes, including mesenchymal stem cells, muscle cells, neurons, and haemolymph cells. In particular, we identified a diverse repertoire of neurons in the striated adductor muscle, but not in the smooth muscle. We further reconstructed the cell differentiation events using all the cell clusters by single-cell pseudotemporal trajectories. By integrating dual BrdU-PCNA immunodetection, neuron-specific staining and electron microscopy observation, we showed the spatial distribution of mesenchymal stem cells and neurons in striated adductor muscle of scallops. The present findings will not only be useful to address the cell type-specific gene expression profiles in scallop muscles, but also provide valuable resources for cross-species comparison of marine organisms.     

Double immunocytochemical labeling of cell and tissue samples with monoclonal anti-bromodeoxyuridine

We describe a new monoclonal antibody (designated Bu20a) against bromodeoxyuridine (BrdU). This antibody was selected by screening against human tissues using the APAAP technique, and shows no crossreactivity with normal nuclei. It stains BrdU incorporated into the nuclei of a wide range of cell types, including human tonsil lymphoid cells, normal mouse tissues, and human tumors growing in nude mice. A double-labeling technique is described using this antibody in which cell smears or tissue sections are first labeled by an immunoperoxidase procedure for a cellular antigen (e.g., mouse or human histocompatibility class II antigen, T-lymphocyte antigen, keratin) and BrdU is then detected by indirect immunofluorescence. This procedure, which was applied to a variety of human and animal cells and tissues, is of wide potential value in analyzing the phenotype of S-phase cells and in co-localizing antigen expression and BrdU incorporation in tissue sections.     

Zebrafish neural tube morphogenesis requires Scribble-dependent oriented cell divisions

How control of subcellular events in single cells determines morphogenesis on the scale of the tissue is largely unresolved. The stereotyped cross-midline mitoses of progenitors in the zebrafish neural keel provide a unique experimental paradigm for defining the role and control of single-cell orientation for tissue-level morphogenesis in vivo. We show here that the coordinated orientation of individual progenitor cell division in the neural keel is the cellular determinant required for morphogenesis into a neural tube epithelium with a single straight lumen. We find that Scribble is required for oriented cell division and that its function in this process is independent of canonical apicobasal and planar polarity pathways. We identify a role for Scribble in controlling clustering of α-catenin foci in dividing progenitors. Loss of either Scrib or N-cadherin results in abnormally oriented mitoses, reduced cross-midline cell divisions, and similar neural tube defects. We propose that Scribble-dependent nascent cell-cell adhesion clusters between neuroepithelial progenitors contribute to define orientation of their cell division. Finally, our data demonstrate that while oriented mitoses of individual cells determine neural tube architecture, the tissue can in turn feed back on its constituent cells to define their polarization and cell division orientation to ensure robust tissue morphogenesis.