CAREER: Integrated molecular and computational sensing (IMACS) for label-free bacteriomics

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The PI proposes novel compressed sensing and parallel acquisition imaging approaches to monitor many cells (~thousands) and obtain the unique molecular barcodes via surface enhanced and normal Raman imaging (SERI & NRI) with a throughput advantage ~1000X over existing Raman techniques. Instead of point-scan as used in current confocal Raman microscopy, multi-foci and compressed-sensing snapshot Raman imaging are proposed. To realize large area SERI over mm2, the PI engineers a new class of highly reliable plasmonic surface with hierarchical nanoarchitecture to selectively image cell surfaces and internal organelles (for identification and counting), cell-secreted proteins, enzymes and exotoxins in the extracellular environment (for virulence and biofilm formation assessment), as well as biofilm growth and heterogeneity. Multivariate computational algorithms will be developed and employed in molecular detection and identification, separation of biological fluorescence background, and spatio-spectro-temporal feature extraction, pattern recognition and library matching. IMACS could enable label-free investigation of bacterial sporulation and germination at the population level and network behavior such as quorum sensing and its role in the secretion or recruitment of extracellular factors. IMACS could provide critical information for biolfilm maturation and heterogeneity.