scholarly journals Mesenchymal stem cell subpopulations and their heterogeneity of response to inductions revealed by single-cell RNA-seq

2021 ◽  
Author(s):  
Wenfei Jin ◽  
Wenhong Hou ◽  
Li Duan ◽  
Changyuan Huang ◽  
Xingfu LI ◽  
...  
Keyword(s):  
Single Cell ◽  
Umbilical Cord ◽  
Stromal Cells ◽  
Clinical Applications ◽  
Single Cell Level ◽  
Rna Seq ◽  
Cell Level ◽  
Cell Source ◽  
Cell Subpopulations ◽  
Different Tissues

Mesenchymal stem/stromal cells (MSCs) are promising cell source for regenerative medicine and treatment of autoimmune disorders. Comparing MSCs from different tissues at single cell level is fundamental for optimizing clinical applications. Here we analyzed single cell RNA-seq data of MSCs from 4 tissues, namely umbilical cord, bone marrow, synovial tissue and adipose tissue. We identified 3 major cell subpopulations, namely osteo-MSCs, chondro-MSCs, adipo/myo-MSCs, across all MSC samples. MSCs from umbilical cord exhibited the highest immunosuppression, potentially indicating it is the best immune modulator for autoimmune diseases. The differentiation potentials of MSC subpopulations, which are strongly associated with their subtypes and tissue sources, showed pronounced subpopulation differences. We found MSC subpopulations expanded and differentiated when their subtypes consist with induction directions, while the other subpopulations shrank. We identified the genes and transcription factors underlying each induction at single cell level and subpopulation level, providing better targets for improving induction efficiency.

scholarly journals Cross-Tissue Characterization of Heterogeneities of Mesenchymal Stem Cells and Their Differentiation Potentials

2021 ◽  
Vol 9 ◽  
Author(s):  
Wenhong Hou ◽  
Li Duan ◽  
Changyuan Huang ◽  
Xingfu Li ◽  
Xiao Xu ◽  
...  
Keyword(s):  
Single Cell ◽  
Umbilical Cord ◽  
Stromal Cells ◽  
Tissue Characterization ◽  
Single Cell Level ◽  
Rna Seq ◽  
Cell Level ◽  
Cell Sources ◽  
Cell Subpopulations

Mesenchymal stem/stromal cells (MSCs) are promising cell sources for regenerative medicine and the treatment of autoimmune disorders. Comparing MSCs from different tissues at the single-cell level is fundamental for optimizing clinical applications. Here we analyzed single-cell RNA-seq data of MSCs from four tissues, namely umbilical cord, bone marrow, synovial tissue, and adipose tissue. We identified three major cell subpopulations, namely osteo-MSCs, chondro-MSCs, and adipo/myo-MSCs, across all MSC samples. MSCs from the umbilical cord exhibited the highest immunosuppression, potentially indicating it is the best immune modulator for autoimmune diseases. MSC subpopulations, with different subtypes and tissue sources, showed pronounced differences in differentiation potentials. After we compared the cell subpopulations and cell status pre-and-post chondrogenesis induction, osteogenesis induction, and adipogenesis induction, respectively, we found MSC subpopulations expanded and differentiated when their subtypes consist with induction directions, while the other subpopulations shrank. We identified the genes and transcription factors underlying each induction at the single-cell level and subpopulation level, providing better targets for improving induction efficiency.

scholarly journals scAPAdb: a comprehensive database of alternative polyadenylation at single-cell resolution

2021 ◽  
Author(s):  
Sheng Zhu ◽  
Qiwei Lian ◽  
Wenbin Ye ◽  
Wei Qin ◽  
Zhe Wu ◽  
...  
Keyword(s):  
Single Cell ◽  
Alternative Polyadenylation ◽  
Cell Types ◽  
Single Cell Level ◽  
Cell Heterogeneity ◽  
Rna Seq ◽  
Cell Level ◽  
Eukaryotic Gene ◽  
User Friendly ◽  
Different Cell Types

Abstract Alternative polyadenylation (APA) is a widespread regulatory mechanism of transcript diversification in eukaryotes, which is increasingly recognized as an important layer for eukaryotic gene expression. Recent studies based on single-cell RNA-seq (scRNA-seq) have revealed cell-to-cell heterogeneity in APA usage and APA dynamics across different cell types in various tissues, biological processes and diseases. However, currently available APA databases were all collected from bulk 3′-seq and/or RNA-seq data, and no existing database has provided APA information at single-cell resolution. Here, we present a user-friendly database called scAPAdb (http://www.bmibig.cn/scAPAdb), which provides a comprehensive and manually curated atlas of poly(A) sites, APA events and poly(A) signals at the single-cell level. Currently, scAPAdb collects APA information from > 360 scRNA-seq experiments, covering six species including human, mouse and several other plant species. scAPAdb also provides batch download of data, and users can query the database through a variety of keywords such as gene identifier, gene function and accession number. scAPAdb would be a valuable and extendable resource for the study of cell-to-cell heterogeneity in APA isoform usages and APA-mediated gene regulation at the single-cell level under diverse cell types, tissues and species.

scholarly journals Single-cell RNA-seq reveals a concomitant delay in differentiation and cell cycle of aged hematopoietic stem cell

2020 ◽  
Author(s):  
Léonard Hérault ◽  
Mathilde Poplineau ◽  
Adrien Mazuel ◽  
Nadine Platet ◽  
Élisabeth Remy ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Single Cell ◽  
Single Cell Level ◽  
Cell Cycle Regulators ◽  
Potential Mechanism ◽  
Rna Seq ◽  
Cell Level ◽  
Hematopoietic Stem ◽  
Undifferentiated State ◽  
Reference Map

ABSTRACTHematopoietic stem cells (HSCs) are the guarantor of the proper functioning of hematopoiesis due to their incredible diversity of potential. During aging the heterogeneity of mouse HSCs evolves, which contributes to the deterioration of the immune system. Here we address the transcriptional plasticity of HSC upon aging at the single-cell resolution. Through the analysis of 15,000 young and aged transcriptomes, we reveal 15 clusters of HSCs unveiling rare and specific HSC abilities that change with age. Pseudotime ordering complemented with regulon analysis showed that the consecutive differentiation states of HSC are delayed upon aging. By analysing cell cycle at the single cell level we highlight an imbalance of cell cycle regulators of very immature aged HSC that may contribute to their accumulation in an undifferentiated state.Our results therefore establish a reference map of young and old mouse HSC differentiation and reveal a potential mechanism that delay aged HSC differentiation.

scholarly journals Single-Cell Gene Expression Analysis and Evaluation of the Therapeutic Function of Murine Adipose-Derived Stromal Cells (ASCs) from the Subcutaneous and Visceral Compartment

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Dominik Pförringer ◽  
Matthias M. Aitzetmüller ◽  
Elizabeth A. Brett ◽  
Khosrow S. Houschyar ◽  
Richard Schäfer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Wound Healing ◽  
Single Cell ◽  
Stromal Cells ◽  
Single Cell Level ◽  
Cell Level ◽  
Adipose Derived Stromal Cells ◽  
Wound Healing Model ◽  
Healing Model

Introduction. Adipose-derived stromal cells (ASCs) are a promising resource for wound healing and tissue regeneration because of their multipotent properties and cytokine secretion. ASCs are typically isolated from the subcutaneous fat compartment, but can also be obtained from visceral adipose tissue. The data on their equivalence diverges. The present study analyzes the cell-specific gene expression profiles and functional differences of ASCs derived from the subcutaneous (S-ASCs) and the visceral (V-ASCs) compartment. Material and Methods. Subcutaneous and visceral ASCs were obtained from mouse inguinal fat and omentum. The transcriptional profiles of the ASCs were compared on single-cell level. S-ASCs and V-ASCs were then compared in a murine wound healing model to evaluate their regenerative functionality. Results. On a single-cell level, S-ASCs and V-ASCs displayed distinct transcriptional profiles. Specifically, significant differences were detected in genes associated with neoangiogenesis and tissue remodeling (for example, Ccl2, Hif1α, Fgf7, and Igf). In addition, a different subpopulation ecology could be identified employing a cluster model. Nevertheless, both S-ASCs and V-ASCs induced accelerated healing rates and neoangiogenesis in a mouse wound healing model. Conclusion. With similar therapeutic potential in vivo, the significantly different gene expression patterns of ASCs from the subcutaneous and visceral compartments suggest different signaling pathways underlying their efficacy. This study clearly demonstrates that review of transcriptional results in vivo is advisable to confirm the tentative effect of cell therapies.

scholarly journals LINE-1 Retrotransposon expression in cancerous, epithelial and neuronal cells revealed by 5’-single cell RNA-Seq

2021 ◽  
Author(s):  
Wilson McKerrow ◽  
Shane A. Evans ◽  
Azucena Rocha ◽  
John Sedivy ◽  
Nicola Neretti ◽  
...  
Keyword(s):  
Single Cell ◽  
Cancer Cells ◽  
Early Development ◽  
Immune Cells ◽  
Copy Number ◽  
Single Cells ◽  
Single Cell Level ◽  
Rna Seq ◽  
Cell Level ◽  
Mouse Hippocampus

AbstractLINE-1 retrotransposons are known to be expressed in early development, in tumors and in the germline. Less is known about LINE-1 expression at the single cell level, especially outside the context of cancer. Because LINE-1 elements are present at a high copy number, many transcripts that are not driven by the LINE-1 promoter nevertheless terminate at the LINE-1 3’ UTR. Thus, 3’ targeted single cell RNA-seq datasets are not appropriate for studying LINE-1. However, 5’ targeted single cell datasets provide an opportunity to analyze LINE-1 expression at the single cell level. Most LINE-1 copies are 5’ truncated, and a transcript that contains the LINE-1 5’ UTR as its 5’ end is likely to have been transcribed from its promoter. We developed a method, L1-sc (LINE-1 expression for single cells), to quantify LINE-1 expression in 5’ targeted 10x genomics single cell RNA-seq datasets. Our method confirms that LINE-1 expression is high in cancer cells, but low or absent from immune cells. We also find that LINE-1 expression is elevated in epithelial compared to immune cells outside of the context of cancer and that it is also elevated in neurons compared to glia in the mouse hippocampus.

scholarly journals A step towards enzyme-free tissue dissociation

2019 ◽  
Vol 5 (1) ◽  
pp. 545-548
Author(s):  
Stefan Scheuermann ◽  
Armin Schäfer ◽  
Jens Langejürgen ◽  
Christian Reis
Keyword(s):  
Single Cell ◽  
Stromal Cells ◽  
Processing Time ◽  
Single Cells ◽  
Single Cell Level ◽  
Cell Level ◽  
Tissue Samples ◽  
Tissue Dissociation ◽  
Tissue Matrix ◽  
Generation Sequencing

AbstractThe future of personalized diagnostics commences on the single cell level. Even high-end technologies like Next Generation Sequencing can be improved if applied on pure single cell populations (e.g., tumor cells without contaminating stromal cells) or on a single cell level (DNA/RNA sequencing). The vast majority of these technologies need individual and preferably undistorted cells for the analytical process. Thus, decisive prerequisite for high-end analytics is to remove cells from their tissue matrix as gently as possible. This can be accomplished by an enzyme-free, fast and reproducible approach of generating pure and individual single cells from tissue samples. In this study we demonstrate the utility of a semi-automated Tissue Grinder that is compatible with standard 50 ml centrifuge tubes and standard cell strainer for mechanically, nonenzymatic and parallel processing of tissue samples. We show that without enzymatic treatment viable single-cell yields match or exceed reference enzymatic methods, while reducing processing time by at least 80%.

scholarly journals MAST: A flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA-seq data.

2015 ◽  
Author(s):  
Greg Finak ◽  
Andrew McDavid ◽  
Masanao Yajima ◽  
Jingyuan Deng ◽  
Vivian Gersuk ◽  
...  
Keyword(s):  
Single Cell ◽  
Gene Set Enrichment Analysis ◽  
Cellular Heterogeneity ◽  
Single Cell Level ◽  
Rna Seq ◽  
Linear Modeling ◽  
Cell Level ◽  
Modeling Framework ◽  
Extrinsic Noise ◽  
Transcriptomic Data

Single-cell transcriptomic profiling enables the unprecedented interrogation of gene expression heterogeneity in rare cell populations that would otherwise be obscured in bulk RNA sequencing experiments. The stochastic nature of transcription is revealed in the bimodality of single-cell transcriptomic data, a feature shared across single-cell expression platforms. There is, however, a paucity of computational tools that take advantage of this unique characteristic. We present a new methodology to analyze single-cell transcriptomic data that models this bimodality within a coherent generalized linear modeling framework. We propose a two-part, generalized linear model that allows one to characterize biological changes in the proportions of cells that are expressing each gene, and in the positive mean expression level of that gene. We introduce the cellular detection rate, the fraction of genes turned on in a cell, and show how it can be used to simultaneously adjust for technical variation and so-called “extrinsic noise” at the single-cell level without the use of control genes. Our model permits direct inference on statistics formed by collections of genes, facilitating gene set enrichment analysis. The residuals defined by such models can be manipulated to interrogate cellular heterogeneity and gene-gene correlation across cells and conditions, providing insights into the temporal evolution of networks of co-expressed genes at the single-cell level. Using two single-cell RNA-seq datasets, including newly generated data from Mucosal Associated Invariant T (MAIT) cells, we show how model residuals can be used to identify significant changes across biologically relevant gene sets that are missed by other methods and characterize cellular heterogeneity in response to stimulation.

scholarly journals Dynamic Sex Chromosome Expression in Drosophila Male Germ Cells

2020 ◽  
Author(s):  
Sharvani Mahadevaraju ◽  
Justin M. Fear ◽  
Miriam Akeju ◽  
Brian J. Galletta ◽  
Mara MLS. Pinheiro ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Polymerase Ii ◽  
Germ Cells ◽  
Defense Mechanism ◽  
Sex Chromosome ◽  
Single Cell Level ◽  
Rna Seq ◽  
Cell Level ◽  
Male Germ Cells ◽  
Y Chromosomes

AbstractSex chromosome gene content and expression is unusual. In many organisms the X and Y chromosomes are inactivated in spermatocytes, possibly as a defense mechanism against insertions into unpaired chromatin. In addition to current sex chromosomes, Drosophila has a small gene-poor X-chromosome relic (4th) that re-acquired autosomal status. Using single cell RNA-Seq, we demonstrate that the single X and pair of 4th chromosomes are specifically inactivated in primary spermatocytes. In contrast, genes on the single Y chromosome become maximally active in primary spermatocytes. Reduced X steady-state transcript levels are due to failed activation of RNA-Polymerase-II by phosphorylation of Serine 2 and 5.One Sentence SummarySex chromosome expression during spermatogenesis at the single cell level

scholarly journals Identification of ALP+/CD73+ defining markers for enhanced osteogenic potential in human adipose-derived mesenchymal stromal cells by mass cytometry

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Daisy D. Canepa ◽  
Elisa A. Casanova ◽  
Eirini Arvaniti ◽  
Vinko Tosevski ◽  
Sonja Märsmann ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Osteogenic Differentiation ◽  
Single Cell ◽  
Mesenchymal Stromal Cells ◽  
Stromal Cells ◽  
Osteogenic Potential ◽  
Single Cell Level ◽  
Cellular Composition ◽  
Cell Level ◽  
Differentiation Potential

Abstract Background The impressive progress in the field of stem cell research in the past decades has provided the ground for the development of cell-based therapy. Mesenchymal stromal cells obtained from adipose tissue (AD-MSCs) represent a viable source for the development of cell-based therapies. However, the heterogeneity and variable differentiation ability of AD-MSCs depend on the cellular composition and represent a strong limitation for their use in therapeutic applications. In order to fully understand the cellular composition of MSC preparations, it would be essential to analyze AD-MSCs at single-cell level. Method Recent advances in single-cell technologies have opened the way for high-dimensional, high-throughput, and high-resolution measurements of biological systems. We made use of the cytometry by time-of-flight (CyTOF) technology to explore the cellular composition of 17 human AD-MSCs, interrogating 31 markers at single-cell level. Subcellular composition of the AD-MSCs was investigated in their naïve state as well as during osteogenic commitment, via unsupervised dimensionality reduction as well as supervised representation learning approaches. Result This study showed a high heterogeneity and variability in the subcellular composition of AD-MSCs upon isolation and prolonged culture. Algorithm-guided identification of emerging subpopulations during osteogenic differentiation of AD-MSCs allowed the identification of an ALP+/CD73+ subpopulation of cells with enhanced osteogenic differentiation potential. We could demonstrate in vitro that the sorted ALP+/CD73+ subpopulation exhibited enhanced osteogenic potential and is moreover fundamental for osteogenic lineage commitment. We finally showed that this subpopulation was present in freshly isolated human adipose-derived stromal vascular fractions (SVFs) and that could ultimately be used for cell therapies. Conclusion The data obtained reveal, at single-cell level, the heterogeneity of AD-MSCs from several donors and highlight how cellular composition impacts the osteogenic differentiation capacity. The marker combination (ALP/CD73) can not only be used to assess the differentiation potential of undifferentiated AD-MSC preparations, but also could be employed to prospectively enrich AD-MSCs from the stromal vascular fraction of human adipose tissue for therapeutic applications.

Sign in / Sign up

Export Citation Format

Share Document