scholarly journals Single cell transcriptomics reveals the heterogeneity of the human cornea to identify novel markers of the limbus and stroma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pere Català ◽  
Nathalie Groen ◽  
Jasmin A. Dehnen ◽  
Eduardo Soares ◽  
Arianne J. H. van Velthoven ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Human Cornea ◽  
Corneal Tissue ◽  
Corneal Epithelial ◽  
Disease States ◽  
Heterogeneous Tissue ◽  
Cell Niche ◽  
Different Cell Types ◽  
Regenerative Therapies

AbstractThe cornea is the clear window that lets light into the eye. It is composed of five layers: epithelium, Bowman’s layer, stroma, Descemet’s membrane and endothelium. The maintenance of its structure and transparency are determined by the functions of the different cell types populating each layer. Attempts to regenerate corneal tissue and understand disease conditions requires knowledge of how cell profiles vary across this heterogeneous tissue. We performed a single cell transcriptomic profiling of 19,472 cells isolated from eight healthy donor corneas. Our analysis delineates the heterogeneity of the corneal layers by identifying cell populations and revealing cell states that contribute in preserving corneal homeostasis. We identified expression of CAV1, HOMER3 and CPVL in the corneal epithelial limbal stem cell niche, CKS2, STMN1 and UBE2C were exclusively expressed in highly proliferative transit amplifying cells, CXCL14 was expressed exclusively in the suprabasal/superficial limbus, and NNMT was exclusively expressed by stromal keratocytes. Overall, this research provides a basis to improve current primary cell expansion protocols, for future profiling of corneal disease states, to help guide pluripotent stem cells into different corneal lineages, and to understand how engineered substrates affect corneal cells to improve regenerative therapies.

scholarly journals A single cell transcriptome atlas reveals the heterogeneity of the healthy human cornea and identifies novel markers of the corneal limbus and stroma

2021 ◽  
Author(s):  
Pere Catala ◽  
Nathalie Groen ◽  
Jasmin A Dehnen ◽  
Eduardo Soares ◽  
Arianne JH van Velthoven ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Human Cornea ◽  
Corneal Tissue ◽  
Healthy Human ◽  
Disease States ◽  
Cell Niche ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
Different Cell Types

The cornea is the clear window that lets light into the eye. It is composed of five layers: epithelium, Bowman layer, stroma, Descemet membrane and endothelium. The maintenance of its structure and transparency are determined by the functions of the different cell types populating each layer. Attempts to regenerate corneal tissue and understand disease conditions requires knowledge of how cell profiles vary across this heterogeneous tissue. We performed a single cell transcriptomic profiling of 19,472 cells isolated from eight healthy donor corneas. Our analysis delineates the heterogeneity of the corneal layers by identifying cell populations and revealing cell states that contribute in preserving corneal homeostasis. We identified that the expression of CAV1, CXCL14, HOMER3 and CPVL were exclusive to the corneal epithelial limbal stem cell niche, CKS2, STMN1 and UBE2C were exclusively expressed in highly proliferative transit amplifying cells, and NNMT was exclusively expressed by stromal keratocytes. Overall, this research provides a basis to improve current primary cell expansion protocols, for future profiling of corneal disease states, to help guide pluripotent stem cells into different corneal lineages, and to understand how engineered substrates affect corneal cells to improve regenerative therapies.

scholarly journals Molecular characteristics and spatial distribution of adult human corneal cell subtypes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ann J. Ligocki ◽  
Wen Fury ◽  
Christian Gutierrez ◽  
Christina Adler ◽  
Tao Yang ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cross Sections ◽  
Cell Types ◽  
Marker Genes ◽  
Molecular Characteristics ◽  
Transcriptional Level ◽  
Human Cornea ◽  
Adult Human ◽  
And Migration

AbstractBulk RNA sequencing of a tissue captures the gene expression profile from all cell types combined. Single-cell RNA sequencing identifies discrete cell-signatures based on transcriptomic identities. Six adult human corneas were processed for single-cell RNAseq and 16 cell clusters were bioinformatically identified. Based on their transcriptomic signatures and RNAscope results using representative cluster marker genes on human cornea cross-sections, these clusters were confirmed to be stromal keratocytes, endothelium, several subtypes of corneal epithelium, conjunctival epithelium, and supportive cells in the limbal stem cell niche. The complexity of the epithelial cell layer was captured by eight distinct corneal clusters and three conjunctival clusters. These were further characterized by enriched biological pathways and molecular characteristics which revealed novel groupings related to development, function, and location within the epithelial layer. Moreover, epithelial subtypes were found to reflect their initial generation in the limbal region, differentiation, and migration through to mature epithelial cells. The single-cell map of the human cornea deepens the knowledge of the cellular subsets of the cornea on a whole genome transcriptional level. This information can be applied to better understand normal corneal biology, serve as a reference to understand corneal disease pathology, and provide potential insights into therapeutic approaches.

scholarly journals A fate-mapping approach reveals the composite origin of the connecting tubule and alerts on “single-cell”-specific KO model of the distal nephron

2016 ◽  
Vol 311 (5) ◽  
pp. F901-F906 ◽  
Author(s):  
Francesco Trepiccione ◽  
Christelle Soukaseum ◽  
Anna Iervolino ◽  
Federica Petrillo ◽  
Miriam Zacchia ◽  
...  
Keyword(s):  
Single Cell ◽  
Kidney Development ◽  
Fluorescent Protein ◽  
Collecting Duct ◽  
Yellow Fluorescent Protein ◽  
Cell Types ◽  
Intercalated Cells ◽  
Distal Nephron ◽  
Principal Cells ◽  
Different Cell Types

The distal nephron is a heterogeneous part of the nephron composed by six different cell types, forming the epithelium of the distal convoluted (DCT), connecting, and collecting duct. To dissect the function of these cells, knockout models specific for their unique cell marker have been created. However, since this part of the nephron develops at the border between the ureteric bud and the metanephric mesenchyme, the specificity of the single cell markers has been recently questioned. Here, by mapping the fate of the aquaporin 2 (AQP2) and Na+-Cl−cotransporter (NCC)-positive cells using transgenic mouse lines expressing the yellow fluorescent protein fluorescent marker, we showed that the origin of the distal nephron is extremely composite. Indeed, AQP2-expressing precursor results give rise not only to the principal cells, but also to some of the A- and B-type intercalated cells and even to cells of the DCT. On the other hand, some principal cells and B-type intercalated cells can develop from NCC-expressing precursors. In conclusion, these results demonstrate that the origin of different cell types in the distal nephron is not as clearly defined as originally thought. Importantly, they highlight the fact that knocking out a gene encoding for a selective functional marker in the adult does not guarantee cell specificity during the overall kidney development. Tools allowing not only cell-specific but also time-controlled recombination will be useful in this sense.

scholarly journals Single-cell transcriptome analysis of tumor and stromal compartments of pancreatic ductal adenocarcinoma primary tumors and metastatic lesions

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Wei Lin ◽  
Pawan Noel ◽  
Erkut H. Borazanci ◽  
Jeeyun Lee ◽  
Albert Amini ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Cell Types ◽  
Ductal Adenocarcinoma ◽  
Cellular Composition ◽  
Primary Tumors ◽  
Metastatic Lesions ◽  
Tumor Tissues ◽  
Cell Type Specific ◽  
Different Cell Types

Abstract Background Solid tumors such as pancreatic ductal adenocarcinoma (PDAC) comprise not just tumor cells but also a microenvironment with which the tumor cells constantly interact. Detailed characterization of the cellular composition of the tumor microenvironment is critical to the understanding of the disease and treatment of the patient. Single-cell transcriptomics has been used to study the cellular composition of different solid tumor types including PDAC. However, almost all of those studies used primary tumor tissues. Methods In this study, we employed a single-cell RNA sequencing technology to profile the transcriptomes of individual cells from dissociated primary tumors or metastatic biopsies obtained from patients with PDAC. Unsupervised clustering analysis as well as a new supervised classification algorithm, SuperCT, was used to identify the different cell types within the tumor tissues. The expression signatures of the different cell types were then compared between primary tumors and metastatic biopsies. The expressions of the cell type-specific signature genes were also correlated with patient survival using public datasets. Results Our single-cell RNA sequencing analysis revealed distinct cell types in primary and metastatic PDAC tissues including tumor cells, endothelial cells, cancer-associated fibroblasts (CAFs), and immune cells. The cancer cells showed high inter-patient heterogeneity, whereas the stromal cells were more homogenous across patients. Immune infiltration varies significantly from patient to patient with majority of the immune cells being macrophages and exhausted lymphocytes. We found that the tumor cellular composition was an important factor in defining the PDAC subtypes. Furthermore, the expression levels of cell type-specific markers for EMT+ cancer cells, activated CAFs, and endothelial cells significantly associated with patient survival. Conclusions Taken together, our work identifies significant heterogeneity in cellular compositions of PDAC tumors and between primary tumors and metastatic lesions. Furthermore, the cellular composition was an important factor in defining PDAC subtypes and significantly correlated with patient outcome. These findings provide valuable insights on the PDAC microenvironment and could potentially inform the management of PDAC patients.

scholarly journals Cell-type-specific analysis of alternative polyadenylation using single-cell transcriptomics data

2019 ◽  
Vol 47 (19) ◽  
pp. 10027-10039 ◽  
Author(s):  
Eldad David Shulman ◽  
Ran Elkon
Keyword(s):  
Gene Regulation ◽  
Single Cell ◽  
Alternative Polyadenylation ◽  
Cell Types ◽  
Protein Coding ◽  
Multiple Datasets ◽  
Transcriptomics Data ◽  
Cell Type Specific ◽  
Transcriptional Gene Regulation ◽  
Different Cell Types

AbstractAlternative polyadenylation (APA) is emerging as an important layer of gene regulation because the majority of mammalian protein-coding genes contain multiple polyadenylation (pA) sites in their 3′ UTR. By alteration of 3′ UTR length, APA can considerably affect post-transcriptional gene regulation. Yet, our understanding of APA remains rudimentary. Novel single-cell RNA sequencing (scRNA-seq) techniques allow molecular characterization of different cell types to an unprecedented degree. Notably, the most popular scRNA-seq protocols specifically sequence the 3′ end of transcripts. Building on this property, we implemented a method for analysing patterns of APA regulation from such data. Analyzing multiple datasets from diverse tissues, we identified widespread modulation of APA in different cell types resulting in global 3′ UTR shortening/lengthening and enhanced cleavage at intronic pA sites. Our results provide a proof-of-concept demonstration that the huge volume of scRNA-seq data that accumulates in the public domain offers a unique resource for the exploration of APA based on a very broad collection of cell types and biological conditions.

Tissue distribution of primary metabolism between epidermal, mesophyll and parenchymatous bundle sheath cells in barley leaves

2000 ◽  
Vol 27 (9) ◽  
pp. 747 ◽  
Author(s):  
Olga A. Koroleva ◽  
A. Deri Tomos ◽  
John Farrar ◽  
Peter Roberts ◽  
Christopher J. Pollock
Keyword(s):  
Single Cell ◽  
Sucrose Solution ◽  
Sucrose Concentration ◽  
Cell Types ◽  
Bundle Sheath ◽  
Assimilate Transport ◽  
Primary Metabolism ◽  
Diurnal Changes ◽  
Radioactive Label ◽  
Different Cell Types

This paper originates from a presentation at the International Conference on Assimilate Transport and Partitioning, Newcastle, NSW, August 1999 In order to investigate the roles of different cell types, metabolite compartmentation in barley (Hordeum vulgare L.) leaf tissue was mapped at the single-cell level, using single-cell sampling and analysis (SiCSA) techniques. The partitioning of recently fixed photoassimilate was investigated for the first time at single-cell resolution, using BAMS (biological accelerator mass spectroscopy) for precise measurement of 14C in femtomole quantities. The data obtained by BAMS qualitatively reflect concentrations of sugars in different cell types measured by SiCSA. Calculation of 14C-specific activities showed that the radioactive label saturated the mesophyll and parenchymatous bundle sheath (PBS) pools within the 45-min labelling period. During the photoperiod, sucrose concentration increased to 200 mM in mesophyll cells. The concentration of malate also increased during the photoperiod in mesophyll and PBS cells. Epidermal cells contained very low concentrations of sugar but high concentrations of malate (120–180 mM) and did not show significant diurnal changes. Accumulation of sugars and fructan synthesis could be induced in mesophyll and PBS cells by reduced export of sugars from leaves or, alternatively, when sugars were supplied from excised leaf blade bases immersed in a sucrose solution in the dark. The epidermis accumulated additional malate in step with the accumulation of sugar by the mesophyll/PBS cells during the long-term reduction of export. Immunolocalisation of Rubisco and cytochrome oxidase proteins was used to analyse the distribution of enzymes of photoassimilation and respiration between functionally different cells in mature leaves of barley.

scholarly journals Molecular comparison of single cell MDA products derived from different cell types

2009 ◽  
Vol 19 (1) ◽  
pp. 89-98 ◽  
Author(s):  
Stavros Glentis ◽  
Sioban SenGupta ◽  
Alan Thornhill ◽  
Rubin Wang ◽  
Ian Craft ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Molecular Comparison ◽  
Different Cell Types

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 Computational approaches towards reducing contamination in single-cell RNA-seq data

2020 ◽  
Author(s):  
Siamak Yousefi ◽  
Hao Chen ◽  
Jesse F. Ingels ◽  
Melinda S. McCarty ◽  
Arthur G. Centeno ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Real Life ◽  
Cell Types ◽  
Cell Capture ◽  
Rna Seq ◽  
Sequence Analyses ◽  
Cell Functions ◽  
Biological Interpretation ◽  
Different Cell Types

SUMMARYSingle cell RNA sequencing has enabled quantification of single cells and identification of different cell types and subtypes as well as cell functions in different tissues. Single cell RNA sequence analyses assume acquired RNAs correspond to cells, however, RNAs from contamination within the input data are also captured by these assays. The sequencing of background contamination as well as unwanted cells making their way to the final assay Potentially confound the correct biological interpretation of single cell transcriptomic data. Here we demonstrate two approaches to deal with background contamination as well as profiling of unwanted cells in the assays. We use three real-life datasets of whole-cell capture and nucleotide single-cell captures generated by Fluidigm and 10x technologies and show that these methods reduce the effect of contamination, strengthen clustering of cells and improves biological interpretation.

scholarly journals Mapping multicellular programs from single-cell profiles

2020 ◽  
Author(s):  
Livnat Jerby-Arnon ◽  
Aviv Regev
Keyword(s):  
Single Cell ◽  
Spatial Data ◽  
Spatial Information ◽  
Single Cells ◽  
Cell Types ◽  
Risk Genes ◽  
Health And Disease ◽  
Different Cell Types ◽  
Cellular Components ◽  
Acting In Concert

ABSTRACTTissue homeostasis relies on orchestrated multicellular circuits, where interactions between different cell types dynamically balance tissue function. While single-cell genomics identifies tissues’ cellular components, deciphering their coordinated action remains a major challenge. Here, we tackle this problem through a new framework of multicellular programs: combinations of distinct cellular programs in different cell types that are coordinated together in the tissue, thus forming a higher order functional unit at the tissue, rather than only cell, level. We develop the open-access DIALOGUE algorithm to systematically uncover such multi-cellular programs not only from spatial data, but even from tissue dissociated and profiled as single cells, e.g., by single-cell RNA-Seq. Tested on spatial transcriptomes from the mouse hypothalamus, DIALOGUE recovered spatial information, predicted the properties of a cell’s environment only based on its transcriptome, and identified multicellular programs that mark animal behavior. Applied to brain samples and colon biopsies profiled by scRNA-Seq, DIALOGUE identified multicellular configurations that mark Alzheimer’s disease and ulcerative colitis (UC), including a program spanning five cell types that is predictive of response to anti-TNF therapy in UC patients and enriched for UC risk genes from GWAS, each acting in different cell types, but all cells acting in concert. Taken together, our study provides a novel conceptual and methodological framework to unravel multicellular regulation in health and disease.

Sign in / Sign up

Export Citation Format

Share Document