Monday, April 29, 2024
4/29/2024
Project summary Although fluorescence microscopy has matured into a prevalent imaging method for biomedical researchers, fluorescence spectroscopy exhibits several fundamental limitations: (1) lack of composition information; (2) inability of imaging small biomolecules; (3) color barrier of multiplexing imaging; (4) lack of chemical sensitivity. To this end, the advent of stimulated Raman scattering (SRS) microscopy have revolutionized chemical imaging. Most importantly, recent developments have proven that SRS microscopy can be complimentary to fluorescence in addressing the above-mentioned limitations: (1) revealing chemical compositions by targeting their endogenous chemical bonds; (2) employing a set of bioorthogonal vibrational tags (such as C=C, C=N, carbon-deuterium C-D and 13C isotope) to image small biomolecules; (3) presenting an appealing strategy to surpass the “color barrier” when coupled with super-multiplexed probes; (4) containing information about structure and dynamics of the target molecule, as well as its interaction with environment. Although SRS has the promise to emerge as the next major modality in biophotonics, its utility has been limited in the following two major aspects. First, the sensitivity of SRS microscopy has reached an impasse. Currently, the detection limit cannot image many important small analytes and chemical drugs inside cells, which are below the concentration of 100 micromolar. Second, although SRS is compatible with live cell biology, the application of SRS inside live cells is significantly under-explored, largely due to that the available probes for SRS imaging are seriously lagging behind. As such, many advanced applications of chemical imaging have not been realized. We propose to develop the next-generation, ultrasensitive SRS microscopy by integrating innovations from imaging instrumentation, probe chemistry and data science. We will employ a new laser source to push SRS microscopy to the nanomolar range for small fundamental chemical bonds. Meanwhile, we will systematically develop a library of responsive Raman sensors that can enter live cells and monitor important analytes there. Moreover, we will deploy newly developed machine learning algorithms to further assist live-cell imaging. When fully optimized, this will bring SRS microscopy to the ultimate sensitivity (comparable to that of fluorescence microscopy), and fully open the application in live cell biology.
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