While differential sensing has the potential to discriminate millions to trillions of analytes based on hundreds of sensing elements, most of the current differential sensor arrays have limited scalability, with only a handful of recognition elements demonstrated. Here we demonstrate a novel differential sensor array based on a class of organic/inorganic hybrid fluorophores, DNA-templated silver nanoclusters (DNA/Ag NCs), that not only has great scalability but also combine both recognition element and signal transduction element into one unit. Six DNA/Ag NC sensors were designed to classify the lysates of six breast epithelial and cancer cell lines with distinct metastatic potential. While MDA-MB-231 and MCF7 lysates showed significantly different fluorescence signatures upon interaction with the sensor array, other cell lines were also differentiable. Our method is simple, versatile, low-cost, reliable, and scalable.
Since surface-enhanced Raman spectroscopy (SERS) makes it possible to enhance weak Raman signals which represent molecular own vibrational transition as a fingerprint, it has gotten much attention in the field of biosensor. Although SERS can detect specific molecules with high sensitivity and selectivity, it is still difficult to fabricate efficient SERS substrates, align ‘hot-spot’ with a detection site, and increase reproducibility for molecular sensing. Here, we converged plasmonic trapping with conventional SERS in order to overcome these drawbacks. As plasmonic trapping is to move nano particles toward the desired position by electric field gradient, we could trap gold nano particles (GNPs) onto a raw bowtie substrate and fabricate self-aligned hot-spots by using plasmonic trapping, which is directly contributed to enhancing weak signals by shortening structure-to-structure distances. Also, since a united laser was used to trap GNPs and to detect target molecules at the same time, it was possible to directly obtain Raman signal on the self-aligned hotspots. To further verify our technique, we also conducted numerical analysis for electric field distribution and trapping force by using finite element method and the results were well matched with the experimental data. This increases low reproducibility of SERS and as a result, we could repetitively obtain same results.
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