SERS-active nanostructures incorporated into a microfluidic device have been developed for rapid and multiplex monitoring of selected Type 1 cytokine (interleukins: IL-6, IL-8, IL-18) levels in blood plasma. Multiple analyses have been performed by using nanoparticles, each coated with different Raman reporter molecules: 5,5′-dithio-bis(2-nitro-benzoic acid) (DTNB), fuchsin (FC), and p-mercatpobenzoic acid (p-MBA) and with specific antibodies. The multivariate statistical method, principal component analysis (PCA), was applied for segregation of three different antigen-antibody complexes encoded by three Raman reporters (FC, p-MBA, and DTNB) during simultaneous multiplexed detection approach. To the best of our knowledge, we have also presented, for the first time, a possibility for multiplexed quantification of three interleukins: IL-6, IL-8, and IL-18 in blood plasma samples using SERS technique. Our method improves the detection limit in comparison to standard ELISA methods. The low detection limits were estimated to be 2.3 pg·ml⁻¹, 6.5 pg·ml⁻¹, and 4.2 pg·ml⁻¹ in a parallel approach, and 3.8 pg·ml⁻¹, 7.5 pg·ml⁻¹, and 5.2 pg·ml⁻¹ in a simultaneous multiplexed method for IL-6, IL-8, and IL-18, respectively. This demonstrated the sensitivity and reproducibility desirable for analytical examinations.

An ultrasensitive surface-enhanced Raman scattering (SERS) immunoassay based on diatom biosilica with integrated gold nanoparticles (AuNPs) for the detection of interleukin 8 (IL-8) in blood plasma has been developed. The SERS sensing originates from unique features of the diatom frustules, which are capable of enhancing the localized surface-plasmon resonance of metal nanostructures. The SERS immune tags ware fabricated by functionalizing 70-nm Au nanoparticles with DTNB (i.e., 5,5′-dithiobis(2-nitrobenzoic acid)), which acted as a Raman reporter molecule, as well as the specific antibodies. These DTNB-labeled immune-AuNPs can form a sandwich structure with IL-8 antigens (infection marker) and the antibodies immobilized on the biosilica material. Our method showed an improved IL-8 detection limit in comparison to standard ELISA methods. The current detection limit for IL-8 using a conventional ELISA test is about 15.6 pg mL⁻¹. The lower detection limit for IL-8 in blood plasma was estimated to be 6.2 pg mL⁻¹. To the best of our knowledge, this is the first report on the recognition of IL-8 in human samples using a SERS-based method. This method clearly possesses high sensitivity to clinically relevant interleukin concentrations in body fluids. The average relative standard deviation of this method is less than 8%, which is sufficient for analytical analysis and comparable to those of classical ELISA methods. This SERS immunoassay also exhibits high biological specificity for the detection of IL-8 antigens. The established SERS immunoassay offers a valuable platform for the ultrasensitive and highly specific detection of immune biomarkers in a clinical setting for medical diagnostics. The SERS-based immunoassay based on naturally generated photonic biosilica for the detection of interleukin 8 (IL-8) in human plasma samples

The detection and monitoring of circulating tumor cells (CTCs) in blood is an important strategy for early cancer evidence, analysis, monitoring of therapeutic response, and optimization of cancer therapy treatments. In this work, tailor-made membranes (MBSP) for surface-enhanced Raman spectroscopy (SERS)-based analysis, which permitted the separation and enrichment of CTCs from blood samples, were developed. A thin layer of SERS-active metals deposited on polymer mat enhanced the Raman signals of CTCs and provided further insight into CTCs molecular and biochemical composition. The SERS spectra of all studied cells—prostate cancer (PC3), cervical carcinoma (HeLa), and leucocytes as an example of healthy (normal) cell—revealed significant differences in both the band positions and/or their relative intensities. The multivariate statistical technique based on principal component analysis (PCA) was applied to identify the most significant differences (marker bands) in SERS data among the analyzed cells and to perform quantitative analysis of SERS data. Based on a developed PCA algorithm, the studied cell types were classified with an accuracy of 95% in 2D PCA to 98% in 3D PCA. These results clearly indicate the diagnostic efficiency for the discrimination between cancer and normal cells. In our approach, we exploited the one-step technology that exceeds most of the multi-stage CTCs analysis methods used and enables simultaneous filtration, enrichment, and identification of the tumor cells from blood specimens.

A new class of SERS substrates is presented that allows for the simultaneous filtration of bacteria from any solution (blood, urine, water, or milk), immobilization of bacteria on the SERS platform, and enhancing the Raman signal of bacteria.