Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes

Understanding the diversity and evolution of eukaryotic microorganisms remains one of the major challenges of modern biology. In recent years, we have advanced in the discovery and phylogenetic placement of new eukaryotic species and lineages, which in turn completely transformed our view on the euk...

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Detalles Bibliográficos
Autores: Ku, Chuan, Sebé-Pedrós, Arnau
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2019
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/44148
Acceso en línea:http://hdl.handle.net/10230/44148
http://dx.doi.org/10.1098/rstb.2019.0098
Access Level:acceso abierto
Palabra clave:Gene expression analysis
scRNA-seq
Environmental sampling
Protists
Unicellular eukaryotes
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spelling Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotesKu, ChuanSebé-Pedrós, ArnauGene expression analysisscRNA-seqEnvironmental samplingProtistsUnicellular eukaryotesUnderstanding the diversity and evolution of eukaryotic microorganisms remains one of the major challenges of modern biology. In recent years, we have advanced in the discovery and phylogenetic placement of new eukaryotic species and lineages, which in turn completely transformed our view on the eukaryotic tree of life. But we remain ignorant of the life cycles, physiology and cellular states of most of these microbial eukaryotes, as well as of their interactions with other organisms. Here, we discuss how high-throughput genome-wide gene expression analysis of eukaryotic single cells can shed light on protist biology. First, we review different single-cell transcriptomics methodologies with particular focus on microbial eukaryote applications. Then, we discuss single-cell gene expression analysis of protists in culture and what can be learnt from these approaches. Finally, we envision the application of single-cell transcriptomics to protist communities to interrogate not only community components, but also the gene expression signatures of distinct cellular and physiological states, as well as the transcriptional dynamics of interspecific interactions. Overall, we argue that single-cell transcriptomics can significantly contribute to our understanding of the biology of microbial eukaryotes. This article is part of a discussion meeting issue 'Single cell ecology'.Royal Society20202019info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/44148http://dx.doi.org/10.1098/rstb.2019.0098reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésPhilos Trans R Soc Lond B Biol Sci. 2019; 374(1786):20190098© The Royal Society http://dx.doi.org/10.1098/rstb.2019.0098info:eu-repo/semantics/openAccessoai:recercat.cat:10230/441482026-05-29T05:05:01Z
dc.title.none.fl_str_mv Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes
title Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes
spellingShingle Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes
Ku, Chuan
Gene expression analysis
scRNA-seq
Environmental sampling
Protists
Unicellular eukaryotes
title_short Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes
title_full Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes
title_fullStr Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes
title_full_unstemmed Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes
title_sort Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes
dc.creator.none.fl_str_mv Ku, Chuan
Sebé-Pedrós, Arnau
author Ku, Chuan
author_facet Ku, Chuan
Sebé-Pedrós, Arnau
author_role author
author2 Sebé-Pedrós, Arnau
author2_role author
dc.subject.none.fl_str_mv Gene expression analysis
scRNA-seq
Environmental sampling
Protists
Unicellular eukaryotes
topic Gene expression analysis
scRNA-seq
Environmental sampling
Protists
Unicellular eukaryotes
description Understanding the diversity and evolution of eukaryotic microorganisms remains one of the major challenges of modern biology. In recent years, we have advanced in the discovery and phylogenetic placement of new eukaryotic species and lineages, which in turn completely transformed our view on the eukaryotic tree of life. But we remain ignorant of the life cycles, physiology and cellular states of most of these microbial eukaryotes, as well as of their interactions with other organisms. Here, we discuss how high-throughput genome-wide gene expression analysis of eukaryotic single cells can shed light on protist biology. First, we review different single-cell transcriptomics methodologies with particular focus on microbial eukaryote applications. Then, we discuss single-cell gene expression analysis of protists in culture and what can be learnt from these approaches. Finally, we envision the application of single-cell transcriptomics to protist communities to interrogate not only community components, but also the gene expression signatures of distinct cellular and physiological states, as well as the transcriptional dynamics of interspecific interactions. Overall, we argue that single-cell transcriptomics can significantly contribute to our understanding of the biology of microbial eukaryotes. This article is part of a discussion meeting issue 'Single cell ecology'.
publishDate 2019
dc.date.none.fl_str_mv 2019
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/44148
http://dx.doi.org/10.1098/rstb.2019.0098
url http://hdl.handle.net/10230/44148
http://dx.doi.org/10.1098/rstb.2019.0098
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Philos Trans R Soc Lond B Biol Sci. 2019; 374(1786):20190098
dc.rights.none.fl_str_mv © The Royal Society http://dx.doi.org/10.1098/rstb.2019.0098
info:eu-repo/semantics/openAccess
rights_invalid_str_mv © The Royal Society http://dx.doi.org/10.1098/rstb.2019.0098
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Royal Society
publisher.none.fl_str_mv Royal Society
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
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