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An optimised tissue disaggregation and data processing pipeline for characterising fibroblast phenotypes using single-cell RNA sequencing

An optimised tissue disaggregation and data processing pipeline for characterising fibroblast phenotypes using single-cell RNA sequencing
An optimised tissue disaggregation and data processing pipeline for characterising fibroblast phenotypes using single-cell RNA sequencing
Single-cell RNA sequencing (scRNA-Seq) provides a valuable platform for characterising multicellular ecosystems. Fibroblasts are a heterogeneous cell type involved in many physiological and pathological processes, but remain poorly-characterised. Analysis of fibroblasts is challenging: these cells are difficult to isolate from tissues, and are therefore commonly under-represented in scRNA-seq datasets. Here, we describe an optimised approach for fibroblast isolation from human lung tissues. We demonstrate the potential for this procedure in characterising stromal cell phenotypes using scRNA-Seq, analyse the effect of tissue disaggregation on gene expression, and optimise data processing to improve clustering quality. We also assess the impact of in vitro culture conditions on stromal cell gene expression and proliferation, showing that altering these conditions can skew phenotypes.
2045-2322
Waise, Sara
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Parker, Rachel
4b5f0253-6a22-4693-b3ae-57295c7409c2
Rose-Zerilli, Matthew
08b3afa4-dbc2-4c0d-a852-2a9f33431199
Layfield, David
9e0fbad6-2b96-468b-bf4e-366e92d5dcb4
Wood, Oliver
dad2f90c-70a5-44a0-914a-52809b75d1c6
West, Jonathon
488375c9-0e7a-4e5f-877f-5d6c145c3f7f
Ottensmeier, Christian
42b8a398-baac-4843-a3d6-056225675797
Thomas, Gareth
2ff54aa9-a766-416b-91ee-cf1c5be74106
Hanley, Christopher
7e2d840d-e724-4389-a362-83741ccdf241
Waise, Sara
13f667c5-853e-4120-a2c6-bbc8324e3b2a
Parker, Rachel
4b5f0253-6a22-4693-b3ae-57295c7409c2
Rose-Zerilli, Matthew
08b3afa4-dbc2-4c0d-a852-2a9f33431199
Layfield, David
9e0fbad6-2b96-468b-bf4e-366e92d5dcb4
Wood, Oliver
dad2f90c-70a5-44a0-914a-52809b75d1c6
West, Jonathon
488375c9-0e7a-4e5f-877f-5d6c145c3f7f
Ottensmeier, Christian
42b8a398-baac-4843-a3d6-056225675797
Thomas, Gareth
2ff54aa9-a766-416b-91ee-cf1c5be74106
Hanley, Christopher
7e2d840d-e724-4389-a362-83741ccdf241

Waise, Sara, Parker, Rachel, Rose-Zerilli, Matthew, Layfield, David, Wood, Oliver, West, Jonathon, Ottensmeier, Christian, Thomas, Gareth and Hanley, Christopher (2019) An optimised tissue disaggregation and data processing pipeline for characterising fibroblast phenotypes using single-cell RNA sequencing. Scientific Reports, 9, [9580]. (doi:10.1038/s41598-019-45842-4).

Record type: Article

Abstract

Single-cell RNA sequencing (scRNA-Seq) provides a valuable platform for characterising multicellular ecosystems. Fibroblasts are a heterogeneous cell type involved in many physiological and pathological processes, but remain poorly-characterised. Analysis of fibroblasts is challenging: these cells are difficult to isolate from tissues, and are therefore commonly under-represented in scRNA-seq datasets. Here, we describe an optimised approach for fibroblast isolation from human lung tissues. We demonstrate the potential for this procedure in characterising stromal cell phenotypes using scRNA-Seq, analyse the effect of tissue disaggregation on gene expression, and optimise data processing to improve clustering quality. We also assess the impact of in vitro culture conditions on stromal cell gene expression and proliferation, showing that altering these conditions can skew phenotypes.

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More information

Accepted/In Press date: 13 June 2019
e-pub ahead of print date: 3 July 2019
Published date: 3 July 2019

Identifiers

Local EPrints ID: 432313
URI: http://eprints.soton.ac.uk/id/eprint/432313
ISSN: 2045-2322
PURE UUID: c39290e9-1afc-4fd4-918b-3cef9639dd7a
ORCID for Matthew Rose-Zerilli: ORCID iD orcid.org/0000-0002-1064-5350
ORCID for Christopher Hanley: ORCID iD orcid.org/0000-0003-3816-7220

Catalogue record

Date deposited: 09 Jul 2019 16:30
Last modified: 10 Jan 2022 03:04

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Contributors

Author: Sara Waise
Author: Rachel Parker
Author: David Layfield
Author: Oliver Wood
Author: Jonathon West
Author: Gareth Thomas

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