Dynamic-SERS optophysiology: a nanosensor for monitoring cell secretion events

We monitored metabolite secretion near living cells using a plasmonic nanosensor. The nanosensor created from borosilicate nanopipettes analogous to the patch clamp was decorated with Au nanoparticles and served as a surface-enhanced Raman scattering (SERS) substrate with addressable location. With...

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Main Authors: Lussier, Félix (Author) , Brulé, Thibault (Author) , Vishwakarma, Medhavi (Author) , Das, Tamal (Author) , Spatz, Joachim P. (Author) , Masson, Jean-François (Author)
Format: Article (Journal)
Language:English
Published: May 12, 2016
In: Nano letters
Year: 2016, Volume: 16, Issue: 6, Pages: 3866-3871
ISSN:1530-6992
DOI:10.1021/acs.nanolett.6b01371
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1021/acs.nanolett.6b01371
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Author Notes:Félix Lussier, Thibault Brulé, Medhavi Vishwakarma, Tamal Das, Joachim P. Spatz, and Jean-François Masson
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Summary:We monitored metabolite secretion near living cells using a plasmonic nanosensor. The nanosensor created from borosilicate nanopipettes analogous to the patch clamp was decorated with Au nanoparticles and served as a surface-enhanced Raman scattering (SERS) substrate with addressable location. With this nanosensor, we acquired SERS locally near Madin-Darby canine kidney (MDCKII) epithelial cells, and we detected multiple metabolites, such as pyruvate, lactate, ATP, and urea simultaneously. These plasmonic nanosensors were capable of monitoring metabolites in the extracellular medium with enough sensitivity to detect an increase in metabolite concentration following the lyses of MDCKII cells with a nonionic surfactant. The plasmonic nanosensors also allowed a relative quantification of a chemical gradient for a metabolite near cells, as demonstrated with a decrease in relative lactate to pyruvate concentration further away from the MDCKII cells. This SERS optophysiology technique for the sensitive and nondestructive monitoring of extracellular metabolites near living cells is broadly applicable to different cellular and tissue models and should therefore provide a powerful tool for cellular studies.
Item Description:Gesehen am 20.05.2020
Physical Description:Online Resource
ISSN:1530-6992
DOI:10.1021/acs.nanolett.6b01371