Exploring Intensity Distributions and Sampling in SERS-Based Immunoassays.

Abstract

Surface-enhanced Raman scattering (SERS) is a sensitive, widely used spectroscopic technique. However, SERS is perceived as poorly reproducible and insufficiently robust for standard applications in analytical chemistry. Here, we demonstrated that reliable SERS immunoassay quantification at low concentrations (pM range) can be achieved by careful experimental design and appropriate data analysis statistics. A SERS-based immunoassay for IgG in human serum (3.1-50.0 ng mL-1 or 20.6-333 pM) was developed as a proof of concept. Calibration curves were created using the population median of the band area, centered at 592 cm-1, of a SERS reporter (Nile Blue A). Histograms of 7200 SERS spectra show lognormal distributions. SEM images of the sensor platform confirm a correlation between the number of SERS probes (ERLs) at the surface and the SERS intensity response. The IgG immunosensor reported here presented a limit of detection of 1.11 ng mL-1 or 7.39 pM and a limit of quantification of 9.04 ng mL-1 or 60.30 pM, within a 95% confidence level. The % error of the predicted versus the actual response of a quality control (QC) sample was 0.13%. The percent error of the QC sample decreases exponentially with the number of measurements. Randomly selected spatially separated measurements provided lower QC % error than a larger number of measurements that were closely spaced. We propose that it is necessary to describe the measured populations using an appropriate sample size for good statistics and consider the interrogation of sufficiently large and well-separated areas of the sensor surface to achieve a reliable sampling.