Multiplexing Metabolomic‐based Disease Diagnosis by Surface Enhanced Raman Spectroscopy (SERS) platform

SERS-based platform has the potential to be successful point-of-care diagnostic tool addressing various human health concerns because it's information-rich, multiplexing, rapid and ease-to-use. SERS has been demonstrated as an ultrasensitive method for detection and identification of molecules at low concentrations without needing fluorescent label. As a signal enhancement method, SERS arises from the well-known Raman cross-section enhancement effect on molecules close to (<5 nm) the surface of nanostructured metal substrates. Since Raman vibration features are uniquely dependent to the molecular structure, SERS platform is a powerful method for identifying biomarkers at near cell membranes and extracellular regions during pathological progression. These attributes allow SERS platform to be a rapid, cell-growth free diagnostic option in urinary tract infections (UTI), sexually transmitted diseases (STD) chlamydia and gonorrhoea, and cancer identification. With both species and strain specificity we will demonstrate the ability of SERS platform to distinguish different bacteria strains, as well as human cancer from normal cells. Combining with multivariate data analysis techniques, expendable reference library and portable instrument, decision can be made with our SERS platform in the clinic within 1–2 hours. Moreover, since we had discovered that the molecular contributors of our SERS vibrational features to be metabolite molecules secreted by the cells in response to environmental change, our SES platform can be a powerful bioanalytical method studying metabolomics in bacteria and human cells more generally. Highlight of ongoing project with our SERS multiplexing, metabolomic-based platform: differentiate STD chlamydia and gonorrhea, UTI diagnosis and human cancer cell identification Highlight of ongoing project with our SERS multiplexing, metabolomic-based platform: differentiate STD chlamydia and gonorrhea, UTI diagnosis and human cancer cell identification