scholarly journals Combining single-cell RNA-sequencing with a molecular atlas unveils new markers for C. elegans neuron classes

2019 ◽  
Author(s):  
Ramiro Lorenzo ◽  
Michiho Onizuka ◽  
Matthieu Defrance ◽  
Patrick Laurent
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Motor Neurons ◽  
Clustering Analysis ◽  
Molecular Signatures ◽  
Functional Diversification ◽  
Genetic Manipulations ◽  
C Elegans ◽  
Single Cell Rna Sequencing

AbstractSingle-cell RNA-sequencing (scRNA-seq) of the Caenorhabditis elegans (C. elegans) nervous system offers the unique opportunity to obtain a partial expression profile for each neuron within a known connectome. Building on recent scRNA-seq data [1] and on a molecular atlas describing the expression pattern of ~800 genes at the single cell resolution [2], we designed an iterative clustering analysis aiming to match each cell-cluster to the ~100 anatomically defined neuron classes of C. elegans. This heuristic approach successfully assigned 58 clusters to their corresponding neuron class. Another 11 clusters grouped neuron classes sharing close molecular signatures and 7 clusters were not assigned. Based on these 76 molecular profiles, we designed 15 new neuron class-specific promoters validated in vivo. Amongst them, 10 represent the only specific promoter reported to this day, expanding the list of neurons amenable to genetic manipulations. Finally, we observed a differential expression of functionally relevant genes between sensory-, inter-, and motor neurons in C. elegans, suggesting the mode of functional diversification may vary accordingly to the neuronal modalities.

scholarly journals Combining single-cell RNA-sequencing with a molecular atlas unveils new markers for Caenorhabditis elegans neuron classes

2020 ◽  
Author(s):  
Ramiro Lorenzo ◽  
Michiho Onizuka ◽  
Matthieu Defrance ◽  
Patrick Laurent
Keyword(s):  
Caenorhabditis Elegans ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Fate ◽  
Single Neuron ◽  
Genetic Manipulations ◽  
C Elegans ◽  
Single Cell Rna Sequencing ◽  
Normal Differentiation

Abstract Single-cell RNA-sequencing (scRNA-seq) of the Caenorhabditis elegans nervous system offers the unique opportunity to obtain a partial expression profile for each neuron within a known connectome. Building on recent scRNA-seq data and on a molecular atlas describing the expression pattern of ∼800 genes at the single cell resolution, we designed an iterative clustering analysis aiming to match each cell-cluster to the ∼100 anatomically defined neuron classes of C. elegans. This heuristic approach successfully assigned 97 of the 118 neuron classes to a cluster. Sixty two clusters were assigned to a single neuron class and 15 clusters grouped neuron classes sharing close molecular signatures. Pseudotime analysis revealed a maturation process occurring in some neurons (e.g. PDA) during the L2 stage. Based on the molecular profiles of all identified neurons, we predicted cell fate regulators and experimentally validated unc-86 for the normal differentiation of RMG neurons. Furthermore, we observed that different classes of genes functionally diversify sensory neurons, interneurons and motorneurons. Finally, we designed 15 new neuron class-specific promoters validated in vivo. Amongst them, 10 represent the only specific promoter reported to this day, expanding the list of neurons amenable to genetic manipulations.

scholarly journals Single-cell RNA sequencing reveals ex vivo signatures of SARS-CoV-2-reactive T cells through ‘reverse phenotyping’

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
David S. Fischer ◽  
Meshal Ansari ◽  
Karolin I. Wagner ◽  
Sebastian Jarosch ◽  
Yiqi Huang ◽  
...  
Keyword(s):  
T Cells ◽  
Single Cell ◽  
Rna Sequencing ◽  
Ex Vivo ◽  
Severe Disease ◽  
Human Leukocyte ◽  
Cell Receptor ◽  
Single Cell Rna Sequencing

AbstractThe in vivo phenotypic profile of T cells reactive to severe acute respiratory syndrome (SARS)-CoV-2 antigens remains poorly understood. Conventional methods to detect antigen-reactive T cells require in vitro antigenic re-stimulation or highly individualized peptide-human leukocyte antigen (pHLA) multimers. Here, we use single-cell RNA sequencing to identify and profile SARS-CoV-2-reactive T cells from Coronavirus Disease 2019 (COVID-19) patients. To do so, we induce transcriptional shifts by antigenic stimulation in vitro and take advantage of natural T cell receptor (TCR) sequences of clonally expanded T cells as barcodes for ‘reverse phenotyping’. This allows identification of SARS-CoV-2-reactive TCRs and reveals phenotypic effects introduced by antigen-specific stimulation. We characterize transcriptional signatures of currently and previously activated SARS-CoV-2-reactive T cells, and show correspondence with phenotypes of T cells from the respiratory tract of patients with severe disease in the presence or absence of virus in independent cohorts. Reverse phenotyping is a powerful tool to provide an integrated insight into cellular states of SARS-CoV-2-reactive T cells across tissues and activation states.

scholarly journals Single-cell RNA sequencing of cultured human endometrial CD140b+CD146+ perivascular cells highlights the importance of in vivo microenvironment

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Dandan Cao ◽  
Rachel W. S. Chan ◽  
Ernest H. Y. Ng ◽  
Kristina Gemzell-Danielsson ◽  
William S. B. Yeung
Keyword(s):  
Stem Cells ◽  
Single Cell ◽  
Rna Sequencing ◽  
Marker Gene ◽  
Cellular Heterogeneity ◽  
Stromal Fibroblast ◽  
Perivascular Cells ◽  
Endometrial Cells ◽  
Single Cell Rna Sequencing

Abstract Background Endometrial mesenchymal-like stromal/stem cells (eMSCs) have been proposed as adult stem cells contributing to endometrial regeneration. One set of perivascular markers (CD140b&CD146) has been widely used to enrich eMSCs. Although eMSCs are easily accessible for regenerative medicine and have long been studied, their cellular heterogeneity, relationship to primary counterpart, remains largely unclear. Methods In this study, we applied 10X genomics single-cell RNA sequencing (scRNA-seq) to cultured human CD140b+CD146+ endometrial perivascular cells (ePCs) from menstrual and secretory endometrium. We also analyzed publicly available scRNA-seq data of primary endometrium and performed transcriptome comparison between cultured ePCs and primary ePCs at single-cell level. Results Transcriptomic expression-based clustering revealed limited heterogeneity within cultured menstrual and secretory ePCs. A main subpopulation and a small stress-induced subpopulation were identified in secretory and menstrual ePCs. Cell identity analysis demonstrated the similar cellular composition in secretory and menstrual ePCs. Marker gene expression analysis showed that the main subpopulations identified from cultured secretory and menstrual ePCs simultaneously expressed genes marking mesenchymal stem cell (MSC), perivascular cell, smooth muscle cell, and stromal fibroblast. GO enrichment analysis revealed that genes upregulated in the main subpopulation enriched in actin filament organization, cellular division, etc., while genes upregulated in the small subpopulation enriched in extracellular matrix disassembly, stress response, etc. By comparing subpopulations of cultured ePCs to the publicly available primary endometrial cells, it was found that the main subpopulation identified from cultured ePCs was culture-unique which was unlike primary ePCs or primary endometrial stromal fibroblast cells. Conclusion In summary, these data for the first time provides a single-cell atlas of the cultured human CD140b+CD146+ ePCs. The identification of culture-unique relatively homogenous cell population of CD140b+CD146+ ePCs underscores the importance of in vivo microenvironment in maintaining cellular identity.

scholarly journals Single-Cell RNA Sequencing Reveals Renal Endothelium Heterogeneity and Metabolic Adaptation to Water Deprivation

2019 ◽  
Vol 31 (1) ◽  
pp. 118-138 ◽  
Author(s):  
Sébastien J. Dumas ◽  
Elda Meta ◽  
Mila Borri ◽  
Jermaine Goveia ◽  
Katerina Rohlenova ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Endothelial Cell ◽  
Oxidative Phosphorylation ◽  
Single Cell ◽  
Rna Sequencing ◽  
Water Deprivation ◽  
Metabolic Adaptation ◽  
Single Cell Rna Sequencing

BackgroundRenal endothelial cells from glomerular, cortical, and medullary kidney compartments are exposed to different microenvironmental conditions and support specific kidney processes. However, the heterogeneous phenotypes of these cells remain incompletely inventoried. Osmotic homeostasis is vitally important for regulating cell volume and function, and in mammals, osmotic equilibrium is regulated through the countercurrent system in the renal medulla, where water exchange through endothelium occurs against an osmotic pressure gradient. Dehydration exposes medullary renal endothelial cells to extreme hyperosmolarity, and how these cells adapt to and survive in this hypertonic milieu is unknown.MethodsWe inventoried renal endothelial cell heterogeneity by single-cell RNA sequencing >40,000 mouse renal endothelial cells, and studied transcriptome changes during osmotic adaptation upon water deprivation. We validated our findings by immunostaining and functionally by targeting oxidative phosphorylation in a hyperosmolarity model in vitro and in dehydrated mice in vivo.ResultsWe identified 24 renal endothelial cell phenotypes (of which eight were novel), highlighting extensive heterogeneity of these cells between and within the cortex, glomeruli, and medulla. In response to dehydration and hypertonicity, medullary renal endothelial cells upregulated the expression of genes involved in the hypoxia response, glycolysis, and—surprisingly—oxidative phosphorylation. Endothelial cells increased oxygen consumption when exposed to hyperosmolarity, whereas blocking oxidative phosphorylation compromised endothelial cell viability during hyperosmotic stress and impaired urine concentration during dehydration.ConclusionsThis study provides a high-resolution atlas of the renal endothelium and highlights extensive renal endothelial cell phenotypic heterogeneity, as well as a previously unrecognized role of oxidative phosphorylation in the metabolic adaptation of medullary renal endothelial cells to water deprivation.

scholarly journals Biological and Medical Importance of Cellular Heterogeneity Deciphered by Single-Cell RNA Sequencing

Cells ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1751 ◽  
Author(s):  
Rishikesh Kumar Gupta ◽  
Jacek Kuznicki
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Future Directions ◽  
Strong Basis ◽  
Bodily Fluids ◽  
Single Cell Rna Sequencing

The present review discusses recent progress in single-cell RNA sequencing (scRNA-seq), which can describe cellular heterogeneity in various organs, bodily fluids, and pathologies (e.g., cancer and Alzheimer’s disease). We outline scRNA-seq techniques that are suitable for investigating cellular heterogeneity that is present in cell populations with very high resolution of the transcriptomic landscape. We summarize scRNA-seq findings and applications of this technology to identify cell types, activity, and other features that are important for the function of different bodily organs. We discuss future directions for scRNA-seq techniques that can link gene expression, protein expression, cellular function, and their roles in pathology. We speculate on how the field could develop beyond its present limitations (e.g., performing scRNA-seq in situ and in vivo). Finally, we discuss the integration of machine learning and artificial intelligence with cutting-edge scRNA-seq technology, which could provide a strong basis for designing precision medicine and targeted therapy in the future.

scholarly journals The novel BET inhibitor UM-002 reduces glioblastoma cell proliferation and invasion

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Anna M. Jermakowicz ◽  
Matthew J. Rybin ◽  
Robert K. Suter ◽  
Jann N. Sarkaria ◽  
Zane Zeier ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Single Cell ◽  
Rna Sequencing ◽  
Ex Vivo ◽  
Adult Brain ◽  
Bet Inhibitor ◽  
Bet Inhibitors ◽  
Single Cell Rna Sequencing

AbstractBromodomain and extraterminal domain (BET) proteins have emerged as therapeutic targets in multiple cancers, including the most common primary adult brain tumor glioblastoma (GBM). Although several BET inhibitors have entered clinical trials, few are brain penetrant. We have generated UM-002, a novel brain penetrant BET inhibitor that reduces GBM cell proliferation in vitro and in a human cerebral brain organoid model. Since UM-002 is more potent than other BET inhibitors, it could potentially be developed for GBM treatment. Furthermore, UM-002 treatment reduces the expression of cell-cycle related genes in vivo and reduces the expression of invasion related genes within the non-proliferative cells present in tumors as measured by single cell RNA-sequencing. These studies suggest that BET inhibition alters the transcriptional landscape of GBM tumors, which has implications for designing combination therapies. Importantly, they also provide an integrated dataset that combines in vitro and ex vivo studies with in vivo single-cell RNA-sequencing to characterize a novel BET inhibitor in GBM.

scholarly journals Combined transient ablation and single cell RNA sequencing reveals the development of medullary thymic epithelial cells

2020 ◽  
Author(s):  
Kristen L. Wells ◽  
Corey N. Miller ◽  
Andreas R. Gschwind ◽  
Wu Wei ◽  
Jonah D. Phipps ◽  
...  
Keyword(s):  
Epithelial Cells ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Critical Role ◽  
Lineage Tracing ◽  
Thymic Epithelial Cells ◽  
Single Cell Rna Sequencing ◽  
Medullary Thymic Epithelial Cells

AbstractMedullary thymic epithelial cells (mTECs) play a critical role in central immune tolerance by mediating negative selection of autoreactive T cells through the collective expression of the peripheral self-antigen compartment, including tissue-specific antigens (TSAs). Recent work has shown that gene expression patterns within the mTEC compartment are remarkably heterogenous and include multiple differentiated cell states. To further define mTEC development and medullary epithelial lineage relationships, we combined lineage tracing and recovery from transient in vivo mTEC ablation with single cell RNA-sequencing. The combination of bioinformatic and experimental approaches revealed a non-stem transit-amplifying population of cycling mTECs that preceded Aire expression. Based on our findings, we propose a branching model of mTEC development wherein a heterogeneous pool of transit-amplifying cells gives rise to Aire- and Ccl21a-expressing mTEC subsets. We further use experimental techniques to show that within the Aire-expressing developmental branch, TSA expression peaked as Aire expression decreased, implying Aire expression must be established before TSA expression can occur. Collectively, these data provide a higher order roadmap of mTEC development and demonstrate the power of combinatorial approaches leveraging both in vivo models and high-dimensional datasets.

scholarly journals Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression

2019 ◽  
Author(s):  
Anna SE Cuomo ◽  
Daniel D Seaton ◽  
Davis J McCarthy ◽  
Iker Martinez ◽  
Marc Jan Bonder ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cell Fate ◽  
Cell Biology ◽  
Population Variation ◽  
Ips Cell ◽  
Cell Fate Decisions ◽  
Common Genetic Variants ◽  
Single Cell Rna Sequencing

AbstractRecent developments in stem cell biology have enabled the study of cell fate decisions in early human development that are impossible to study in vivo. However, understanding how development varies across individuals and, in particular, the influence of common genetic variants during this process has not been characterised. Here, we exploit human iPS cell lines from 125 donors, a pooled experimental design, and single-cell RNA-sequencing to study population variation of endoderm differentiation. We identify molecular markers that are predictive of differentiation efficiency, and utilise heterogeneity in the genetic background across individuals to map hundreds of expression quantitative trait loci that influence expression dynamically during differentiation and across cellular contexts.

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