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Single-cell transcriptomic profiling provides insights into retinal endothelial barrier properties

PURPOSE: To better characterize retinal endothelial barrier properties through analysis of individual transcriptomes of primary bovine retinal microvascular endothelial cells (RMECs). METHODS: Individual RMECs were captured on the Fluidigm C1 system, cDNA libraries were prepared using a Nextera XT k...

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Autores principales: Watson, Mark I., Barabas, Peter, McGahon, Mary, McMahon, Megan, Fuchs, Marc A., Curtis, Tim M., Simpson, David A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Vision 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7765706/
https://www.ncbi.nlm.nih.gov/pubmed/33380778
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author Watson, Mark I.
Barabas, Peter
McGahon, Mary
McMahon, Megan
Fuchs, Marc A.
Curtis, Tim M.
Simpson, David A.
author_facet Watson, Mark I.
Barabas, Peter
McGahon, Mary
McMahon, Megan
Fuchs, Marc A.
Curtis, Tim M.
Simpson, David A.
author_sort Watson, Mark I.
collection PubMed
description PURPOSE: To better characterize retinal endothelial barrier properties through analysis of individual transcriptomes of primary bovine retinal microvascular endothelial cells (RMECs). METHODS: Individual RMECs were captured on the Fluidigm C1 system, cDNA libraries were prepared using a Nextera XT kit, and sequencing was performed on a NextSeq system (Illumina). Data analysis was performed using R packages Scater, SC3, and Seurat, and the browser application Automated Single-cell Analysis Pipeline (ASAP). Alternative splicing events in single cells were quantified with Outrigger. Cytoscape was used for network analyses. RESULTS: Application of a single-cell RNA sequencing (scRNA-seq) analysis workflow showed that RMECs form a relatively homogeneous population in culture, with the main differences related to proliferation status. Expression of markers from along the arteriovenous tree suggested that most cells originated from capillaries. Average gene expression levels across all cells were used to develop an in silico model of the inner blood–retina barrier incorporating junctional proteins not previously reported within the retinal vasculature. Correlation of barrier gene expression among individual cells revealed a subgroup of genes highly correlated with PECAM-1 at the center of the correlation network. Numerous alternative splicing events involving exons within microvascular barrier genes were observed, and in many cases, individual cells expressed one isoform exclusively. CONCLUSIONS: We optimized a workflow for single-cell transcriptomics in primary RMECs. The results provide fundamental insights into the genes involved in formation of the retinal–microvascular barrier.
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spelling pubmed-77657062020-12-29 Single-cell transcriptomic profiling provides insights into retinal endothelial barrier properties Watson, Mark I. Barabas, Peter McGahon, Mary McMahon, Megan Fuchs, Marc A. Curtis, Tim M. Simpson, David A. Mol Vis Research Article PURPOSE: To better characterize retinal endothelial barrier properties through analysis of individual transcriptomes of primary bovine retinal microvascular endothelial cells (RMECs). METHODS: Individual RMECs were captured on the Fluidigm C1 system, cDNA libraries were prepared using a Nextera XT kit, and sequencing was performed on a NextSeq system (Illumina). Data analysis was performed using R packages Scater, SC3, and Seurat, and the browser application Automated Single-cell Analysis Pipeline (ASAP). Alternative splicing events in single cells were quantified with Outrigger. Cytoscape was used for network analyses. RESULTS: Application of a single-cell RNA sequencing (scRNA-seq) analysis workflow showed that RMECs form a relatively homogeneous population in culture, with the main differences related to proliferation status. Expression of markers from along the arteriovenous tree suggested that most cells originated from capillaries. Average gene expression levels across all cells were used to develop an in silico model of the inner blood–retina barrier incorporating junctional proteins not previously reported within the retinal vasculature. Correlation of barrier gene expression among individual cells revealed a subgroup of genes highly correlated with PECAM-1 at the center of the correlation network. Numerous alternative splicing events involving exons within microvascular barrier genes were observed, and in many cases, individual cells expressed one isoform exclusively. CONCLUSIONS: We optimized a workflow for single-cell transcriptomics in primary RMECs. The results provide fundamental insights into the genes involved in formation of the retinal–microvascular barrier. Molecular Vision 2020-11-27 /pmc/articles/PMC7765706/ /pubmed/33380778 Text en Copyright © 2020 Molecular Vision. http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited, used for non-commercial purposes, and is not altered or transformed.
spellingShingle Research Article
Watson, Mark I.
Barabas, Peter
McGahon, Mary
McMahon, Megan
Fuchs, Marc A.
Curtis, Tim M.
Simpson, David A.
Single-cell transcriptomic profiling provides insights into retinal endothelial barrier properties
title Single-cell transcriptomic profiling provides insights into retinal endothelial barrier properties
title_full Single-cell transcriptomic profiling provides insights into retinal endothelial barrier properties
title_fullStr Single-cell transcriptomic profiling provides insights into retinal endothelial barrier properties
title_full_unstemmed Single-cell transcriptomic profiling provides insights into retinal endothelial barrier properties
title_short Single-cell transcriptomic profiling provides insights into retinal endothelial barrier properties
title_sort single-cell transcriptomic profiling provides insights into retinal endothelial barrier properties
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7765706/
https://www.ncbi.nlm.nih.gov/pubmed/33380778
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