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dc.contributor.advisorCheng, Ji-Xinen_US
dc.contributor.authorHuang, Kai-Chihen_US
dc.date.accessioned2020-02-11T20:05:36Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/2144/39329
dc.description.abstractUnderstanding cellular heterogeneity has been a challenge in biology. Current bio-analytical methods such as mass spectrometry or fluorescence-based detection would destruct the sample or perturb the functions of targeted molecules. In situ imaging of bio-molecules at single cell level resolves the phenotypes at metabolomics domain, which can address the challenges in studying cellular heterogeneity. Stimulated Raman scattering (SRS) microscopy provides a label-free approach to identify molecules based on the signature of molecular vibrations. However, there are several challenges to overcome in order to use SRS as a single-cell analysis platform with high throughput, high content, and high sensitivity. My thesis work aims to overcome above-mentioned difficulties. To fulfill the first unmet need of single cell metabolic analysis, we developed an SRS flow cytometry, and demonstrated the discrimination of particles at a throughput of up to 11,000 particles per second, which is a four orders of magnitude improvement compared to conventional spontaneous Raman flow cytometry. Next, we addressed the second unmet need of single-cell metabolic analysis through the development of SRS imaging cytometry. Using this platform, we studied the response of human pancreatic cancer to drug-induced and starvation-induced stress, and discovered lipid-facilitated protrusion as a metabolic biomarker for stress-resistant cancer cells. Lastly, to probe low-concentration bio-molecules using fingerprint Raman bands, we utilized pre-resonance enhancement to increase the SRS signal by two orders of magnitude, and demonstrated ultra-sensitive imaging of retinoids in cells. We demonstrated in situ imaging of retinoid level in cancer cells and during neuronal development. Collectively, these efforts demonstrate SRS cytometry as a high-throughput, high-content, and high-sensitivity single-cell analysis platform with broad applications.en_US
dc.language.isoen_US
dc.rightsAttribution-NonCommercial 4.0 Internationalen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectBiomedical engineeringen_US
dc.subjectCoherent Raman scatteringen_US
dc.titleSingle-cell metabolic analysis by stimulated Raman scattering cytometryen_US
dc.typeThesis/Dissertationen_US
dc.date.updated2020-01-29T02:01:38Z
dc.description.embargo2022-01-28T00:00:00Z
etd.degree.nameDoctor of Philosophyen_US
etd.degree.leveldoctoralen_US
etd.degree.disciplineBiomedical Engineeringen_US
etd.degree.grantorBoston Universityen_US
dc.identifier.orcid0000-0002-3419-825X


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Except where otherwise noted, this item's license is described as Attribution-NonCommercial 4.0 International