Ultra-sensitive digital quantification of proteins and mRNA in single cells.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
07 08 2019
Historique:
received: 29 09 2018
accepted: 16 07 2019
entrez: 9 8 2019
pubmed: 9 8 2019
medline: 18 12 2019
Statut: epublish

Résumé

Simultaneous measurement of proteins and mRNA in single cells enables quantitative understanding and modeling of cellular functions. Here, we present an automated microfluidic system for multi-parameter and ultra-sensitive protein/mRNA measurements in single cells. Our technology improves the sensitivity of digital proximity ligation assay by up to 55-fold, with a detection limit of 2277 proteins per cell and with detection efficiency of as few as 29 protein molecules. Our measurements using this system reveal higher mRNA/protein correlation in single mammalian cells than previous estimates. Furthermore, time-lapse imaging of herpes simplex virus 1 infected epithelial cells enabled by our device shows that expression of ICP4 -a major transcription factor regulating hundreds of viral genes- is only partially correlated with viral protein counts, suggesting that many cells go through abortive infection. These results highlight the importance of high-sensitivity protein/mRNA quantification for understanding fundamental molecular mechanisms in individual cells.

Identifiants

pubmed: 31391463
doi: 10.1038/s41467-019-11531-z
pii: 10.1038/s41467-019-11531-z
pmc: PMC6685952
doi:

Substances chimiques

Proteins 0
RNA, Messenger 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't Video-Audio Media

Langues

eng

Sous-ensembles de citation

IM

Pagination

3544

Subventions

Organisme : NIGMS NIH HHS
ID : R01 GM127527
Pays : United States

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Auteurs

Jing Lin (J)

Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, 60637, USA.
Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA.

Christian Jordi (C)

Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, 60637, USA.
Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA.
Department of Biosystems Science and Engineering, ETH Zürich, 4058, Basel, Switzerland.

Minjun Son (M)

Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, 60637, USA.
Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA.

Hoang Van Phan (H)

Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, 60637, USA.
Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA.

Nir Drayman (N)

Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, 60637, USA.
Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA.

Mustafa Fatih Abasiyanik (MF)

Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, 60637, USA.
Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA.

Luke Vistain (L)

Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, 60637, USA.
Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA.

Hsiung-Lin Tu (HL)

Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, 60637, USA.
Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA.
Institute of Chemistry, Academia Sinica, Taipei, 11529, Taiwan.

Savaş Tay (S)

Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, 60637, USA. tays@uchicago.edu.
Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL, 60637, USA. tays@uchicago.edu.

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Classifications MeSH