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Title:Utilizing Raman spectroscopy and multivariate analysis to identify and monitor the differentiation states of individual stem cells
Author(s):Ilin, Yelena
Director of Research:Kraft, Mary L.
Doctoral Committee Chair(s):Kraft, Mary L.
Doctoral Committee Member(s):Bhargava, Rohit; Harley, Brendan A.; Kong, Hyunjoon
Department / Program:Chemical & Biomolecular Engr
Discipline:Chemical Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Raman spectroscopy
Multivariate analysis
Stem cells
Single cell analysis
Abstract:The rapid progression of stem cell research over several decades has resulted in significant advances in disease treatment, particularly for diseases of the blood and bone marrow. While such treatments are beneficial to thousands of patients every year, mankind has not fully harnessed the therapeutic potential of stem cells. One important avenue towards achieving this goal involves using stem cells in native or artificial tissue to promote healthy cell and/or tissue expansion and regeneration. In order to understand the extrinsic factors and mechanisms that influence stem cell fate decisions, complex biomaterial screening platforms have been developed to screen the largest number of factors using the smallest number of rare, primary stem cells. These platforms necessitate analytical tools that can be used to identify the differentiation state of individual cells in order to correlate this information with the local cues acting upon the cell. The standard techniques used for stem cell identification in situ have a number of disadvantages, including the use of potentially toxic fluorescent probes, limitations in the chemical information that can be probed, and subjectivity in data interpretation. The work presented herein investigates the potential of spontaneous Raman microspectroscopy as an objective, non-invasive, marker-free, quantitative technique to chemically characterize and identify individual cells, specifically stem cells and their progeny, with location and time specificity. Chapter 1 presents an introduction and review of these applications. The utility of multivariate analysis of Raman cell spectra towards generating identification models is also discussed. The work presented in Chapter 2 demonstrates that Raman spectroscopy and partial least squares-discriminant analysis can be used to accurately discriminate between individual living or fixed mammalian cells in co-cultures. This methodology was then applied towards identifying the differentiation states of primary hematopoietic stem cells and their progeny when seeded on biomaterial substrates of varying stiffnesses, as presented in Chapter 3. Chapter 4 focuses on utilizing Raman spectroscopy to monitor the neutrophilic differentiation of myeloid cells over time; these results show that biomarkers of discrete differentiation states correlated with specific spectral markers. Ultimately, significant research effort will be required to further optimize this methodology and address its various challenges, including sensitivity, reproducibility, and applicability on different platforms.
Issue Date:2017-04-18
Rights Information:Copyright 2017 Yelena Ilin
Date Available in IDEALS:2017-08-10
Date Deposited:2017-05

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