4.5 Article

Surface-enhanced resonance Raman scattering for the sensitive detection of a tuberculosis biomarker in human serum

Journal

JOURNAL OF RAMAN SPECTROSCOPY
Volume 50, Issue 1, Pages 15-25

Publisher

WILEY
DOI: 10.1002/jrs.5500

Keywords

immunoassay; infectious disease diagnostics; resonance Raman; surface-enhanced Raman scattering; tuberculosis

Categories

Funding

  1. U.S. Food and Drug Administration [U18 FD004034]
  2. Bill and Melinda Gates Foundation [OOP10396210]
  3. National Institutes of Health [R01AI111495, UG3CA211551]
  4. Critical Path Initiative of the U.S. Food and Drug Administration [U18 FD004034]

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Improvements in the detection of biomarkers indicative of disease continue to be vital to human health. Toward this end, this paper presents (a) the development and characterization of a biomarker detection strategy based on the inherently stronger signals generated by surface-enhanced resonance Raman scattering (SERRS), as opposed to surface-enhanced Raman scattering (SERS); (b) the application of this approach to the detection of mannose-capped lipoarabinomannan (ManLAM), an antigenic marker indicative of active tuberculosis infection; and (c) a comparison of readout for this SERRS platform to that of the more frequently used approach based on SERS. More specifically, the work detailed herein describes the design and testing of a SERRS immunoassay that incorporates a resonance Raman-enhanced adlayer of cyanine 5 on a smooth gold capture surface and its application to biomarker detection when turned on by the tagging of captured ManLAM with gold nanoparticle labels. The results of these experiments demonstrated an improvement in the detection of ManLAM spiked into human serum in terms of limit of detection by 10x and analytical sensitivity of almost 40x when compared with SERS. Findings also indicate that these improvements arise primarily from the intrinsic increase in signal strength due to the resonance Raman effect and a small but measurable increase in nanoparticle label density. Potential routes to further improve the performance of this approach to immunoassay signal generation are briefly discussed.

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