Designing a deployable and adaptable plasmonic sensing platform for infectious disease surveillance

SUMMARY This proposal aims to address the critical need for cost-effective, sensitive, and accurate point-of-need (PON) testing for infectious diseases by developing an adaptable and deployable sensing platform. Currently available molecular diagnostic tests, such as polymerase chain reaction (PCR) and lateral flow assays (LFA), exhibit limitations in terms of either ease of deployment or accuracy and sensitivity. This tradeoff between accuracy and cost-effectiveness/distribution has hindered the containment of the current pandemic and could limit our surveillance capabilities of emerging diseases. To overcome these challenges, we propose to develop catalytic surface-enhanced Raman scattering (SERS) sensors based on functional DNA sequences, offering several advantages over existing diagnostic methods. The long-term goal of this project is to create a sensing platform capable of detecting multiple genetic biomarkers in liquid biopsies, enabling effective PON diagnostics. The proposed SERS sensors provide highly multiplexed assays, improving accuracy in pathogen and variant identification. Furthermore, these sensors offer quantifiable results that can be used for prognostic purposes, enabling viral load determination. These SERS sensors are easily deployable and exhibit superior sensitivity compared to LFA, resulting in more accurate PON diagnostic tests. In this project, we plan to leverage inverse design and machine learning techniques to study the key functional DNA features that influence sensor performance. The insights gained for optimal design rules will be used to develop an automated sensor design algorithm capable of producing designs with predictable figures- of-merit, given a target genetic code. Additionally, we aim to exploit the reagentless feature of the sensors by developing lyophilized sensing tablets containing all necessary components for the sensing process. These tablets enable on- demand testing by simply adding the sample, thereby providing a practical means to administer this one-pot SERS assay at the PON. To validate these advancements, a multiplexed assay will be developed to detect SARS-CoV-2 and validated on saliva samples containing various inactivated viruses from different SARS-CoV-2 variants. We will test the diagnostic accuracy in the identification of viral load and specific variants.