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Surface-Enhanced Raman Spectroscopy-Based Label-Free Insulin Detection at Physiological Concentrations for Analysis of Islet Performance

Cho, Hyunjun and Kumar, Shailabh and Yang, Daejong and Vaidyanathan, Sagar R. and Woo, Kelly and Garcia, Ian and Shue, Hao Jan and Yoon, Youngzoon and Ferreri, Kevin and Choo, Hyuck (2018) Surface-Enhanced Raman Spectroscopy-Based Label-Free Insulin Detection at Physiological Concentrations for Analysis of Islet Performance. ACS Sensors, 3 (1). pp. 65-71. ISSN 2379-3694. https://resolver.caltech.edu/CaltechAUTHORS:20180112-131323127

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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.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://dx.doi.org/10.1021/acssensors.7b00864DOIArticle
http://pubs.acs.org/doi/suppl/10.1021/acssensors.7b00864PublisherSupplementary Information
ORCID:
AuthorORCID
Kumar, Shailabh0000-0001-5383-3282
Yang, Daejong0000-0002-8774-5843
Choo, Hyuck0000-0002-8903-7939
Alternate Title:SERS-Based Label-Free Insulin Detection at Physiological Concentrations for Analysis of Islet Performance
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.
Group:Heritage Medical Research Institute
Funders:
Funding AgencyGrant Number
Caltech-City of Hope Collaboration FundUNSPECIFIED
Heritage Medical Research InstituteUNSPECIFIED
Samsung Grand Research OpportunityUNSPECIFIED
Issue or Number:1
Record Number:CaltechAUTHORS:20180112-131323127
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20180112-131323127
Official Citation:Surface-Enhanced Raman Spectroscopy-Based Label-Free Insulin Detection at Physiological Concentrations for Analysis of Islet Performance. Hyunjun Cho, Shailabh Kumar, Daejong Yang, Sagar Vaidyanathan, Kelly Woo, Ian Garcia, Hao J. Shue, Youngzoon Yoon, Kevin Ferreri, and Hyuck Choo. ACS Sensors 2018 3 (1), 65-71. DOI: 10.1021/acssensors.7b00864
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:84304
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:16 Jan 2018 16:36
Last Modified:03 Oct 2019 19:17

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