Published January 26, 2018 | Version Supplemental Material
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Surface-Enhanced Raman Spectroscopy-Based Label-Free Insulin Detection at Physiological Concentrations for Analysis of Islet Performance

Abstract

Label-free optical detection of insulin would allow in vitro assessment of pancreatic cell functions in their natural state and expedite diabetes-related clinical research and treatment; however, no existing method has met these criteria at physiological concentrations. Using spatially uniform 3D gold-nanoparticle sensors, we have demonstrated surface-enhanced Raman sensing of insulin in the secretions from human pancreatic islets under low and high glucose environments without the use of labels such as antibodies or aptamers. Label-free measurements of the islet secretions showed excellent correlation among the ambient glucose levels, secreted insulin concentrations, and measured Raman-emission intensities. When excited at 785 nm, plasmonic hotspots of the densely arranged 3D gold-nanoparticle pillars as well as strong interaction between sulfide linkages of the insulin molecules and the gold nanoparticles produced highly sensitive and reliable insulin measurements down to 100 pM. The sensors exhibited a dynamic range of 100 pM to 50 nM with an estimated detection limit of 35 pM, which covers the reported concentration range of insulin observed in pancreatic cell secretions. The sensitivity of this approach is approximately 4 orders of magnitude greater than previously reported results using label-free optical approaches, and it is much more cost-effective than immunoassay-based insulin detection widely used in clinics and laboratories. These promising results may open up new opportunities for insulin sensing in research and clinical applications.

Additional Information

© 2018 American Chemical Society. Received: November 21, 2017; Accepted: January 11, 2018; Published: January 11, 2018. This work was supported by the Caltech-City-of-Hope Collaboration Fund, Heritage Medical Research Institute, and the Samsung Grand Research Opportunity. The authors declare no competing financial interest.

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Additional details

Additional titles

Alternative title
SERS-Based Label-Free Insulin Detection at Physiological Concentrations for Analysis of Islet Performance

Identifiers

Eprint ID
84304
DOI
10.1021/acssensors.7b00864
Resolver ID
CaltechAUTHORS:20180112-131323127

Related works

Funding

Caltech-City of Hope Collaboration Fund
Heritage Medical Research Institute
Samsung Grand Research Opportunity

Dates

Created
2018-01-16
Created from EPrint's datestamp field
Updated
2021-11-15
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Caltech groups
Heritage Medical Research Institute