Multi-omics Uncover Neonatal Cecal Cell Development Potentials

Abstract BackgroundAlthough, the cecum plays vital roles in absorption of water, electrolytes, and other small molecules, and harbors trillions of commensal bacteria to shape large intestine immune functions, it is unknown the cecum development potentials at single cell level during the very crucial neonatal developmental period.ResultsUsing singe cell RNA-seq and proteomics, we have characterized six major types of cecal epithelial cells: undifferentiated cells; immune cells (Ims); cecumocytes (CCs); goblet, Paneth like cells (PLCs), and enteroendocrine cells (EECs) with specific marker genes. CCs mature with a gradual decrease in number; however, Ims develop with a continuing increase in number. Meanwhile secretory cells (goblet, PLCs, EECs) reduce in number during the neonatal developmental period. The cells exhibit specific development and maturation trends controlled by transcriptional factors, ligand-receptor pairs, and other factors. As piglets grow, cecal content and mucosal microbial diversity increases dramatically with population of beneficial microbiota, such as lactobacillus, increasing significantly. Moreover, cecal mucosal-associated and cecal content microbiota are positively correlated and both show significant correlation with different types of cecal epithelial cells and plasma metabolites. ConclusionsThis is the first presentation of neonatal cecal cell development and maturation naturally at single cell level with transcript, protein, microbiota and metabolism perspectives. Furthermore, this study provides an important tool for the determination of novel interventions in cecal drug delivery and metabolism studies.

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VASC: dimension reduction and visualization of single cell RNA sequencing data by deep variational autoencoder

10.1101/199315 ◽

2017 ◽

Cited By ~ 6

Author(s):

Dongfang Wang ◽

Jin Gu

Keyword(s):

Dimension Reduction ◽

Single Cell ◽

Rna Sequencing ◽

Original Data ◽

Marker Genes ◽

Single Cell Level ◽

Sequencing Data ◽

Cell Level ◽

Variational Autoencoder ◽

Single Cell Rna Sequencing

AbstractSingle cell RNA sequencing (scRNA-seq) is a powerful technique to analyze the transcriptomic heterogeneities in single cell level. It is an important step for studying cell sub-populations and lineages based on scRNA-seq data by finding an effective low-dimensional representation and visualization of the original data. The scRNA-seq data are much noiser than traditional bulk RNA-Seq: in the single cell level, the transcriptional fluctuations are much larger than the average of a cell population and the low amount of RNA transcripts will increase the rate of technical dropout events. In this study, we proposed VASC (deep Variational Autoencoder for scRNA-seq data), a deep multi-layer generative model, for the unsupervised dimension reduction and visualization of scRNA-seq data. It can explicitly model the dropout events and find the nonlinear hierarchical feature representations of the original data. Tested on twenty datasets, VASC shows superior performances in most cases and broader dataset compatibility compared with four state-of-the-art dimension reduction methods. Then, for a case study of pre-implantation embryos, VASC successfully re-establishes the cell dynamics and identifies several candidate marker genes associated with the early embryo development.

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Innate Immune Response to Influenza Virus at Single-Cell Resolution in Human Epithelial Cells Revealed Paracrine Induction of Interferon Lambda 1

Journal of Virology ◽

10.1128/jvi.00559-19 ◽

2019 ◽

Vol 93 (20) ◽

Cited By ~ 18

Author(s):

Irene Ramos ◽

Gregory Smith ◽

Frederique Ruf-Zamojski ◽

Carles Martínez-Romero ◽

Miguel Fribourg ◽

...

Keyword(s):

Public Health ◽

Epithelial Cells ◽

Immune Responses ◽

Single Cell ◽

Influenza A ◽

Respiratory Epithelium ◽

Innate Immune ◽

Single Cell Level ◽

Innate Immune Responses ◽

Cell Level

ABSTRACT Early interactions of influenza A virus (IAV) with respiratory epithelium might determine the outcome of infection. The study of global cellular innate immune responses often masks multiple aspects of the mechanisms by which populations of cells work as organized and heterogeneous systems to defeat virus infection, and how the virus counteracts these systems. In this study, we experimentally dissected the dynamics of IAV and human epithelial respiratory cell interaction during early infection at the single-cell level. We found that the number of viruses infecting a cell (multiplicity of infection [MOI]) influences the magnitude of virus antagonism of the host innate antiviral response. Infections performed at high MOIs resulted in increased viral gene expression per cell and stronger antagonist effect than infections at low MOIs. In addition, single-cell patterns of expression of interferons (IFN) and IFN-stimulated genes (ISGs) provided important insights into the contributions of the infected and bystander cells to the innate immune responses during infection. Specifically, the expression of multiple ISGs was lower in infected than in bystander cells. In contrast with other IFNs, IFN lambda 1 (IFNL1) showed a widespread pattern of expression, suggesting a different cell-to-cell propagation mechanism more reliant on paracrine signaling. Finally, we measured the dynamics of the antiviral response in primary human epithelial cells, which highlighted the importance of early innate immune responses at inhibiting virus spread. IMPORTANCE Influenza A virus (IAV) is a respiratory pathogen of high importance to public health. Annual epidemics of seasonal IAV infections in humans are a significant public health and economic burden. IAV also causes sporadic pandemics, which can have devastating effects. The main target cells for IAV replication are epithelial cells in the respiratory epithelium. The cellular innate immune responses induced in these cells upon infection are critical for defense against the virus, and therefore, it is important to understand the complex interactions between the virus and the host cells. In this study, we investigated the innate immune response to IAV in the respiratory epithelium at the single-cell level, providing a better understanding on how a population of epithelial cells functions as a complex system to orchestrate the response to virus infection and how the virus counteracts this system.

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Normal epithelial cells trigger EphA2-dependent RasV12 cell repulsion at the single cell level

Small GTPases ◽

10.1080/21541248.2017.1324940 ◽

2017 ◽

pp. 1-6 ◽

Cited By ~ 4

Author(s):

William Hill ◽

Catherine Hogan

Keyword(s):

Epithelial Cells ◽

Single Cell ◽

Single Cell Level ◽

Cell Level ◽

Cell Repulsion

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Study of uptake and loss of silica nanoparticles in living human lung epithelial cells at single cell level

Analytical and Bioanalytical Chemistry ◽

10.1007/s00216-009-2839-0 ◽

2009 ◽

Vol 394 (6) ◽

pp. 1595-1608 ◽

Cited By ~ 53

Author(s):

Isaac Stayton ◽

Jeffrey Winiarz ◽

Katie Shannon ◽

Yinfa Ma

Keyword(s):

Epithelial Cells ◽

Single Cell ◽

Silica Nanoparticles ◽

Human Lung ◽

Lung Epithelial Cells ◽

Single Cell Level ◽

Cell Level ◽

Lung Epithelial ◽

Human Lung Epithelial Cells

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Characterization of primary mammary epithelial cells with loss of BRCA1at a single cell level

BMC Proceedings ◽

10.1186/1753-6561-7-s2-p58 ◽

2013 ◽

Vol 7 (S2) ◽

Author(s):

Rebecca E Nakles ◽

Sarah Millman ◽

M Carla Cabrera ◽

Peter Johnson ◽

Susette C Mueller ◽

...

Keyword(s):

Epithelial Cells ◽

Single Cell ◽

Mammary Epithelial Cells ◽

Mammary Epithelial ◽

Single Cell Level ◽

Cell Level

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Single-Cell Transcriptomics Reveals Endothelial Plasticity During Diabetic Atherogenesis

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.689469 ◽

2021 ◽

Vol 9 ◽

Author(s):

Guizhen Zhao ◽

Haocheng Lu ◽

Yuhao Liu ◽

Yang Zhao ◽

Tianqing Zhu ◽

...

Keyword(s):

Endothelial Cell ◽

Cardiovascular Diseases ◽

Single Cell ◽

Single Cells ◽

Marker Genes ◽

Diabetic Patients ◽

Single Cell Level ◽

Biological Functions ◽

Cell Level ◽

Mesenchymal Transition

Atherosclerosis is the leading cause of cardiovascular diseases, which is also the primary cause of mortality among diabetic patients. Endothelial cell (EC) dysfunction is a critical early step in the development of atherosclerosis and aggravated in the presence of concurrent diabetes. Although the heterogeneity of the organ-specific ECs has been systematically analyzed at the single-cell level in healthy conditions, their transcriptomic changes in diabetic atherosclerosis remain largely unexplored. Here, we carried out a single-cell RNA sequencing (scRNA-seq) study using EC-enriched single cells from mouse heart and aorta after 12 weeks feeding of a standard chow or a diabetogenic high-fat diet with cholesterol. We identified eight EC clusters, three of which expressed mesenchymal markers, indicative of an endothelial-to-mesenchymal transition (EndMT). Analyses of the marker genes, pathways, and biological functions revealed that ECs are highly heterogeneous and plastic both in normal and atherosclerotic conditions. The metabolic transcriptomic analysis further confirmed that EndMT-derived fibroblast-like cells are prominent in atherosclerosis, with diminished fatty acid oxidation and enhanced biological functions, including regulation of extracellular-matrix organization and apoptosis. In summary, our data characterized the phenotypic and metabolic heterogeneity of ECs in diabetes-associated atherogenesis at the single-cell level and paves the way for a deeper understanding of endothelial cell biology and EC-related cardiovascular diseases.

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