Design, Rationalization, and Automation of a Catalytic Sensing Mechanism for Homogeneous SERS Biosensors.

The current pandemic has shown that we need sensitive and deployable diagnostic technologies. Surface-enhanced Raman scattering (SERS) sensors can be an ideal solution for developing such advanced point-of-need (PON) diagnostic tests. Homogeneous (reagentless) SERS sensors work by directly responding to the target without any processing step, making them capable for simple one-pot assays, but their limitation is the achievable sensitivity, insufficient compared to what is needed for sensing of viral biomarkers. Noncovalent DNA catalysis mechanisms have been recently exploited for catalytic amplification in SERS assays. These advances used catalytic hairpin assembly (CHA) and other DNA self-assembly processes to develop sensing mechanisms with improved sensitivities. However, these mechanisms have not been used in OFF-to-ON homogeneous sensors, and they often target the same biomarker, likely due to the complexity of the mechanism design. There is still a strong need for a catalytic SERS sensor with a homogeneous mechanism and a rationalization of the catalytic sensing mechanism to translate this sensing strategy to different targets and applications. We developed and investigated a homogeneous SERS sensing mechanism that uses catalytic amplification based on DNA self-assembly. We systematically investigated the role of three domains in the fuel strand (internal loop, stem, and toehold), which drives the catalytic mechanism. The thermodynamic parameters determined in our studies were used to build an algorithm for automated design of catalytic sensors that we validated on target sequences associated with malaria and SARS-CoV-2 strains. With our mechanism, we were able to achieve an amplification level of 20-fold for conventional DNA and of 36-fold using locked nucleic acids (LNAs), with corresponding improvements observed in the sensor limit of detection (LOD). We also show a single-base sequence specificity for a sensor targeting a sequence associated with the omicron variant, tested against a delta variant target. This work on catalytic amplification of homogeneous SERS sensors has the potential to enable the use of this sensing modality in new applications, such as infectious disease surveillance, by improving the LOD while conserving the sensor's homogeneous character.

Platinum Nanoparticle Size and Density Impacts Purine Electrochemistry with Fast-Scan Cyclic Voltammetry.

We demonstrate the density and shape of platinum nanoparticles (PtNP) on carbon-fiber microelectrodes with fast-scan cyclic voltammetry (FSCV) directly impacts detection of adenosine. Previously, we showed that metal nanoparticle-modified carbon significantly improves adenine-based purine detection; however, how the size and shape of the particles impact electrochemical detection was not investigated. Electrochemical investigations of how the surface topology and morphology impacts detection is necessary for designing ultrasensitive electrodes and for expanding fundamental knowledge of electrode-analyte interactions. To change the density and shape of the PtNP's on the surface, we varied the concentration of K2PtCl6 and electrodeposition time. We show that increasing the concentration of K2PtCl6 increases the density of PtNP's while increasing the electrodeposition time impacts both the density and size. These changes manipulate the adsorption behavior which impacts sensitivity. Based on these results, an optimal electrodeposition procedure was determined to be 1.0 mg/mL of K2PtCl6 deposited for 45 s and this results in an average increase in adenosine detection by 3.5 ±0.3-fold. Interestingly, increasing the size and density of PtNPs negatively impacts dopamine detection. Overall, this work provides fundamental insights into the differences between adenosine and dopamine interaction at electrode surfaces.