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Updated: Jun 21, 2026

A Protein Microarray Assay for Serological Determination of Antigen-specific Antibody Responses Following Clostridium difficile Infection
Published on: June 15, 2018
Rapid ultra-sensitive diagnosis of clostridium difficile infection using a SERS-based lateral flow assay
Waleed A Hassanain1, Julia Spoors2, Christopher L Johnson2
1Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, Glasgow, G1 1RD, UK. duncan.graham@strath.ac.uk karen.faulds@strath.ac.uk.
Abstract:
Clostridium difficile (C. diff) infection is one of the most contagious diseases associated with high morbidity and mortality rates in hospitalised patients. Accurate diagnosis can slow its spread by determining the most effective treatment. Herein, we report a novel testing platform as a proof-of-concept for the selective, sensitive, rapid and cost-effective diagnosis of C. diff infection (CDI) based on a duplex measurement. This was achieved by detecting two specific biomarkers, surface layer protein A (SlpA) and toxin B (ToxB), using a surface enhanced Raman scattering-based lateral flow assay (SERS-based LFA). The simultaneous duplex detection of SlpA with ToxB has not been described for the clinical diagnosis of CDI previously. The SlpA biomarker "AKDGSTKEDQLVDALA" was first reported by our group in 2018 as a species-specific identification tool. The second biomarker, ToxB, is the essential virulence biomarker of C. diff pathogenic strains and is required to confirm true infection pathogenicity. The proposed SERS-based LFA platform enabled rapid duplex detection of SlpA and ToxB on separate test lines using a duplex LF test strip within 20 minutes. The use of a handheld Raman spectrometer to scan test lines allowed for the highly sensitive quantitative detection of both biomarkers with a lowest observable concentration of 0.01 pg μL-1. The use of a handheld device in this SERS-based LFA instead of benchtop machine paves the way for rapid, selective, sensitive and cheap clinical evaluation of CDI at the point of care (POC) with minimal sample backlog.
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