Quantitation of metabolic conversions in live cells and in real time is essential to determining how a cell responds to an intervention such as drug treatment or exposure to a risk factor. Nevertheless, most of our knowledge about cellular content is derived from in vitro analysis of isolated cells or measurement of tissue homogenates, either by biochemical assays, omics or sequencing technologies. This gap highlights a need of developing new techniques that are able to repetitively assess the same single cell in a vital organism. We propose to develop a new Raman imaging platform to enable repetitive assessment of single cell metabolism in a vital organism, using C.elegans as a test bed. Our innovation is spectral scanning of a femtosecond pulse at the Fourier plane of an angle-to wavelength pulse shaper, through which a SRS spectrum can be acquired on the scale of 20 ms per pixel. The long-term goal of our research is developing next generation technology to enable quantitative analysis of single live cell response to a stimuli or a treatment in 3D cultures or live animals. The specific objectives of this R21 application are constructing a ms time scale spectroscopic imaging system and longitudinally assessing the fat metabolism in vital C.elegans. An interdisciplinary team has been formed. Dr. Ji-Xin Cheng (PI) is an expert in label-free spectroscopic imaging. Dr. Heidi Tissenbaum (co-PI) is an expert in dissecting molecular mechanisms of the aging process using C.elegans as a model organism. The two investigators have an established collaboration in developing coherent Raman scattering microscopy to study lipid metabolism in live C.elegans. In feasibility studies, the team has demonstrated hyperspectral SRS imaging of lipid oxidation, lipid desaturation, and cholesterol storage in adult worms using fingerprint Raman bands. Moreover, the Cheng lab recently demonstrated spectral modulation SRS imaging with an angle-to- wavelength pulse shaper. Such development paves the foundation for acquisition of a SRS spectrum on the ms time scale. Our hypothesis that ms Raman spectroscopy is able to longitudinally assess lipid metabolism in vital C.elegans during aging, diet restriction or overfeeding. To test this hypothesis, we will design and construct, and test a microsecond Raman spectral imaging with an angle to wavelength pulse shaper. We will then use the system to longitudinally assess energy metabolism of single cells in wild-type and mutant C. elegans. Though C.elegans is used as a test bed, our platform heralds a broader impact on biomedical research via assessing single live cell response to an intervention, including monitoring live cell response to a risk factor or tissue regeneration in response to a stimulus.

Public Health Relevance

We propose to develop a microsecond time scale vibrational spectral imaging platform to enable repetitive assessment of single cell response to an intervention. These capabilities are expected to significantly improve the throughput of drug discovery or risk factor identification.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21GM114853-02
Application #
8934127
Study Section
Special Emphasis Panel (ZRG1-BST-A (50))
Program Officer
Flicker, Paula F
Project Start
2014-09-30
Project End
2016-08-31
Budget Start
2015-09-01
Budget End
2016-08-31
Support Year
2
Fiscal Year
2015
Total Cost
$237,188
Indirect Cost
$61,875
Name
Purdue University
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
072051394
City
West Lafayette
State
IN
Country
United States
Zip Code
47907
Chen, Andy Jing; Yuan, Xiaojing; Li, Junjie et al. (2018) Label-Free Imaging of Heme Dynamics in Living Organisms by Transient Absorption Microscopy. Anal Chem 90:3395-3401
Liao, Chien-Sheng; Cheng, Ji-Xin (2016) In Situ and In Vivo Molecular Analysis by Coherent Raman Scattering Microscopy. Annu Rev Anal Chem (Palo Alto Calif) 9:69-93
Liao, Chien-Sheng; Choi, Joon Hee; Zhang, Delong et al. (2015) Denoising Stimulated Raman Spectroscopic Images by Total Variation Minimization. J Phys Chem C Nanomater Interfaces 119:19397-19403