Enhanced Raman techniques for infection diagnostics
Enhanced Raman techniques for infection diagnostics
In this paper we describe our recent work in multi-excitation surface enhanced Raman spectroscopy (MX-SERS), and its application for robust strain-level bacteria identification. The development of MX-SERS follows directly from our previous work in rapid bacterial identification using multi-excitation Raman spectroscopy (MX-Raman), which enabled highly accurate (up to 99.75%) strain-level distinction of bacteria, including antibiotic resistant strains of bacteria and from within complex media. In this work we use the strong wavelength dependence of both the Raman scattering cross-section and the surface plasmon to demonstrate a novel capability in bacteria identification. Compared to MX-Raman, MX-SERS has up to 8x faster data acquisition speed as well as up to 4000x lower laser power incident on the sample. Furthermore, we fabricate SERS-active substrates with a simple and low-cost fabrication method that can be adapted to fit a chosen wavelength regime. This combination of strain-level sensitivity and high-speed detection, combined with a low-cost SERS substrate, has strong potential applications in clinical diagnostics, and could be integrated within a real-world pathogen detection workflow. This presents new capabilities in label-free bacterial detection including novel culture-free investigation capabilities, and an improved methodology for sample handling with minimal preparation and processing.
Bacterial identification, MX-Raman, Raman spectroscopy, SERS, nanoparticle monolayer
Hanrahan, Niall
df8a0edc-a5bd-4979-aa6f-0ea1bff159c3
Lister, Adam P.
a79ccf69-a17b-4d0a-9fe2-28287e3eddf3
Highmore, Callum J.
04809bd8-7cad-4dcf-b67d-264697f893b9
Rajith, Leena
285b21cf-b298-4b37-9969-b47513d810ca
Avershina, Ekaterina
fd44dafe-430e-4df3-8ed6-432af310db0e
Ali, Jawad
1f81f7eb-0394-411f-8079-440f27d0a5e9
Ahmad, Rafi
3c3766c4-8df4-45d0-bc73-c700882ef207
Webb, Jeremy S.
ec0a5c4e-86cc-4ae9-b390-7298f5d65f8d
Mahajan, Sumeet
3e8fb3d0-f384-4182-ac26-b3063056a3c6
Hanrahan, Niall
df8a0edc-a5bd-4979-aa6f-0ea1bff159c3
Lister, Adam P.
a79ccf69-a17b-4d0a-9fe2-28287e3eddf3
Highmore, Callum J.
04809bd8-7cad-4dcf-b67d-264697f893b9
Rajith, Leena
285b21cf-b298-4b37-9969-b47513d810ca
Avershina, Ekaterina
fd44dafe-430e-4df3-8ed6-432af310db0e
Ali, Jawad
1f81f7eb-0394-411f-8079-440f27d0a5e9
Ahmad, Rafi
3c3766c4-8df4-45d0-bc73-c700882ef207
Webb, Jeremy S.
ec0a5c4e-86cc-4ae9-b390-7298f5d65f8d
Mahajan, Sumeet
3e8fb3d0-f384-4182-ac26-b3063056a3c6
Hanrahan, Niall, Lister, Adam P., Highmore, Callum J., Rajith, Leena, Avershina, Ekaterina, Ali, Jawad, Ahmad, Rafi, Webb, Jeremy S. and Mahajan, Sumeet
(2022)
Enhanced Raman techniques for infection diagnostics.
Verma, Prabhat and Suh, Yung Doug
(eds.)
In Enhanced Spectroscopies and Nanoimaging 2022.
SPIE..
(doi:10.1117/12.2635324).
Record type:
Conference or Workshop Item
(Paper)
Abstract
In this paper we describe our recent work in multi-excitation surface enhanced Raman spectroscopy (MX-SERS), and its application for robust strain-level bacteria identification. The development of MX-SERS follows directly from our previous work in rapid bacterial identification using multi-excitation Raman spectroscopy (MX-Raman), which enabled highly accurate (up to 99.75%) strain-level distinction of bacteria, including antibiotic resistant strains of bacteria and from within complex media. In this work we use the strong wavelength dependence of both the Raman scattering cross-section and the surface plasmon to demonstrate a novel capability in bacteria identification. Compared to MX-Raman, MX-SERS has up to 8x faster data acquisition speed as well as up to 4000x lower laser power incident on the sample. Furthermore, we fabricate SERS-active substrates with a simple and low-cost fabrication method that can be adapted to fit a chosen wavelength regime. This combination of strain-level sensitivity and high-speed detection, combined with a low-cost SERS substrate, has strong potential applications in clinical diagnostics, and could be integrated within a real-world pathogen detection workflow. This presents new capabilities in label-free bacterial detection including novel culture-free investigation capabilities, and an improved methodology for sample handling with minimal preparation and processing.
Text
1220303
- Version of Record
Available under License Other.
More information
e-pub ahead of print date: 3 October 2022
Keywords:
Bacterial identification, MX-Raman, Raman spectroscopy, SERS, nanoparticle monolayer
Identifiers
Local EPrints ID: 472850
URI: http://eprints.soton.ac.uk/id/eprint/472850
PURE UUID: 68a66574-d3b4-4745-9662-339839ac6654
Catalogue record
Date deposited: 20 Dec 2022 17:36
Last modified: 17 Mar 2024 04:06
Export record
Altmetrics
Contributors
Author:
Niall Hanrahan
Author:
Adam P. Lister
Author:
Leena Rajith
Author:
Ekaterina Avershina
Author:
Jawad Ali
Author:
Rafi Ahmad
Author:
Sumeet Mahajan
Editor:
Prabhat Verma
Editor:
Yung Doug Suh
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics