Plant pathogens represent a significant threat to food supplies. Agricultural diagnostics currently function on a paradigm involving either inaccurate visual inspection or burdensome laboratory molecular tests. Several field-ready diagnostic methods have been presented in recent years; however detection of pre-symptomatic or co-occurring infections and in-field sample processing remain challenges. To address these challenges, we developed surface-enhanced Raman scattering (SERS)-sensing hydrogels that uptake pathogenic material (RNA) and produce a measurable response on-site. Our novel reagentless SERS sensor for the detection of tobacco mosaic virus (TMV) was embedded in an environmentally compatible hydrogel material, to produce sensing hydrogels. We demonstrate the diagnostic application of our sensing hydrogels through exposure to TMV infected tobacco plants. This technology offers a field-deployable tool for pre-symptomatic and multiplexed molecular identification of pathogens with the potential to shift the current agricultural diagnostic paradigm.
Point-of-sampling diagnostics has gained interest for its potential to detect trace amounts of analytes in real-time. Several challenges persist with developing accurate and reliable field-testing techniques, including limits of detection, portable and durable instrumentation, and cost effectiveness for routine monitoring. To combat these challenges, our goal is to develop a facile, field deployable Surface-Enhanced Raman Scattering (SERS) sensor for detecting trace amounts of Chemical Warfare Agents (CWAs) and environmental contaminants such as perfluoroalkyl substances (PFAS). In collaboration with the University of Cincinnati, we optimized the ink formulation and printing parameters for AgAu nanostars using a machine learning optimization algorithm to achieve the best SERS performance using the minimal AgAu nanostars. The SERS sensor performance and limits of detection were assessed using CWAs and PFAS. Future work includes exploring the tunability of the LSPR of the AgAu nanostars for compatibility with commercially available handheld Raman spectrometers.
Sandwich-based LFA device was successfully demonstrated to detect salivary lipopolysaccharides of P. gingivalis from human saliva. Although saliva is an attractive biofluid due to non-invasive sampling and excellent availability, isolating targeted biomarkers for analysis in saliva is challenging because of interferences from various biomolecules in saliva, especially by -amylase. Combined pre-treatment using potato starch and syringe filtration has been developed to reduce the interference from -amylase. Pretreated saliva presented a comparable LOD ~46 ng/mL with excellent selectivity versus other LPS and proteins. Future directions include not only the development of aptamer-based LFA but also adapting the Surface Enhanced Raman Scattering (SERS) technology for sensing target analytes in LFA in conjunction with novel silver-coated Au nanostar particles. Our prior research using aptamer in LFA and preliminary results of SERS detection in LFA will be presented to support our future directions.
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