Analysis of multiplexed SERS-based lateral flow assays: turning qualitative into quantitative for inflammatory bowel...

The development of diagnostic tests that offer rapid and quantitative results can improve the health of patients, suffering from both chronic and acute diseases. Inflammatory bowel disease (IBD) is a chronic autoimmune condition, where a patient can undergo periods of sudden flare-ups and prolonged remission. The current biomarkers of interest are either detected using central laboratory methods, or, are non-specific to IBD. In this work, we develop a series of lateral flow immunoassays for the detection of IBD biomarkers lactoferrin and myeloperoxidase, in an artificial stool matrix. By utilising surface enhanced Raman scattering (SERS) active nanotags, we demonstrate the feasibility of these SERS-based lateral flow immunoassays for proof-of-concept singleplex and duplex detection via Raman mapping. Due to the variation in background caused by the stool matrix, we have investigated methods of assessing the SERS signal from the Raman maps, to transition the tests from giving qualitative to quantitative results. This has been achieved by extracting the SERS intensities from the maps associated with non-specific interactions, to define unique intensity thresholds for each lateral flow immunoassay, overall improving the sensitivity, reproducibility, and linearity in limit of detection studies. We achieved limits of detection of 3.2 ng mL^-1 for lactoferrin and 5.0 ng mL^-1 for myeloperoxidase, and limits of quantification of 18.8 ng mL^-1 for lactoferrin and 8.0 ng mL^-1 for myeloperoxidase. These values are well below the "normal" level of these biomarkers in stool, indicating this assay would be able to accurately monitor changing biomarker concentrations. Furthermore, we used a ratiometric approach to evaluate the maps from duplex lateral flows and detect each biomarker simultaneously on the same strip. Overall, this work demonstrates that it is possible to quantitatively detect IBD biomarkers in stool on a lateral flow with SERS, using improved Raman signal analysis methods to overcome complex sample background interference and enhance sensitivity.