Flow cytometry is one of the most important tools for high-throughput single cell analysis. Fluorescent labeling acts as the primary approach for cellular analysis in flow cytometry. Nevertheless, fluorescent tags are not applicable to all cases especially small molecules (e.g. metabolites) for which labeling may significantly perturb their properties. Raman spectroscopic signals arising from inherent molecular vibrations provide a key approach to detect specific molecules inside cells and to differentiate cellular state. Raman-based microfluidic devices have been reported. However, the very small cross section of spontaneous Raman scattering results in low Raman signal level and consequently long data acquisition time, which is not compatible with the high- speed flow condition. The long-term goal of the proposed project is to establish a high-throughput high-content single cell analysis platform using molecular fingerprint vibrations as contrast. The specific objective of current application is to develop a vibrational spectroscopic cytometer based on the stimulated Raman scattering (SRS) process. Several recent advances in the Ji-Xin Cheng (PI) lab, including the highly sensitive femtosecond SRS imaging, lock-in free SRS signal detection and a tuned amplifier array for multiplex SRS imaging, pave the foundation for the planned instrumentation. The PI has assembled an interdisciplinary team for the proposed study. Dr. J. Paul Robinson (co-PI) is a leader in development and applications of fluorescence-based flow cytometer and he will bring expertise to the design of fluidics and multichannel detection systems. Dr. Bartek Rajwa (co-PI) will provide expertise for spectroscopic cytometry data analysis and machine learning. The team will design and construct a SRS flow cytometer by multichannel detection of dispersed SRS signal (Aim 1), construct a tandem system able to collect SRS and fluorescence data (Aim 2), develop spectral un-mixing and machine-learning analysis tools able to combine the information obtained from SRS spectra and labeled biomarkers for functional classification of cells (Aim 3), and validate the capability of SRS flow cytometer for label-free detection of single-cell metabolism (Aim 4). With a speed of analyzing thousands of cells per second, SRS flow cytometer will enable high-throughput analysis of single-cell chemical content which is beyond the reach by fluorescence-based flow cytometer.

Public Health Relevance

We propose to build a high-throughput single cell analysis platform through multiplex stimulated Raman scattering detection of single flowing cells at microsecond time scale. Having fluorescence and stimulated Raman scattering detection in tandem, our platform is capable of discovering new metabolic signatures of cell subpopulations (e.g. cancer stem cells sorted through fluorescent markers). Such discovery could potentially lead to new development of disease-specific treatment strategies.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
7R01GM118471-02
Application #
9320713
Study Section
Instrumentation and Systems Development Study Section (ISD)
Program Officer
Sammak, Paul J
Project Start
2016-08-01
Project End
2020-04-30
Budget Start
2017-05-01
Budget End
2018-04-30
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Boston University
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
049435266
City
Boston
State
MA
Country
United States
Zip Code
02215
Robinson, J Paul (2018) Overview of Flow Cytometry and Microbiology. Curr Protoc Cytom 84:e37
Lee, Hyeon Jeong; Cheng, Ji-Xin (2017) Imaging chemistry inside living cells by stimulated Raman scattering microscopy. Methods 128:119-128
Chen, Xueli; Zhang, Chi; Lin, Peng et al. (2017) Volumetric chemical imaging by stimulated Raman projection microscopy and tomography. Nat Commun 8:15117
Karanja, Caroline W; Hong, Weili; Younis, Waleed et al. (2017) Stimulated Raman Imaging Reveals Aberrant Lipogenesis as a Metabolic Marker for Azole-Resistant Candida albicans. Anal Chem 89:9822-9829
Zhang, Yinxin; Liao, Chien-Sheng; Hong, Weili et al. (2016) Coherent anti-Stokes Raman scattering imaging under ambient light. Opt Lett 41:3880-3
Yue, Shuhua; Cheng, Ji-Xin (2016) Deciphering single cell metabolism by coherent Raman scattering microscopy. Curr Opin Chem Biol 33:46-57
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