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Title:Development of enabling technologies for single cell analysis with mass spectrometry
Author(s):Comi, Troy J
Director of Research:Sweedler, Jonathan V
Doctoral Committee Chair(s):Sweedler, Jonathan V
Doctoral Committee Member(s):Gillette, Martha U; Kraft, Mary L; Lu, Yi
Department / Program:Chemistry
Discipline:Chemistry
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Mass Spectrometry
Single cell analysis
MALDI
desorption electrospray ionization
Abstract:Mass spectrometry (MS) is an effective methodology for untargeted, label-free, highly multiplexed analyses of trace compounds based on their mass-to-charge ratios. For biological applications, these properties have generated interest in determining biomarkers of diseased states, detecting drug compounds and metabolites, and observing previously unknown chemical messengers. Recent developments in instrumentation have provided exquisite sensitivity with robust performance. A growing field of single cell chemical analysis has arisen around these figures of merit. While early reports utilized manual isolation and extraction, recent developments in high-throughput sampling have enabled the examination of large populations of cells. One such method includes the analysis of dispersed single cells on a flat surface. When cells are randomly seeded onto the surface, their locations have to be determined by optical imaging to direct acquisition of isolated cells efficiently. A variety of microprobe ionization sources are suitable for such analyses, though smaller probe footprints can utilize more densely seeded samples. This dissertation describes two technologies for performing single cell analysis with mass spectrometry. The first, synchronized desorption electrospray ionization (DESI), facilitates ambient ionization MS with high mass resolution, low duty cycle mass analyzers. The initial report utilized synchronized DESI for mass spectrometry imaging, but interrupting the desorption plume would be useful for profiling several locations on a surface in an arbitrary order for single cell analysis. The second methodology utilizes microscopy images to guide MS profiling. Specifically, image analysis software, called microMS, was developed to perform cell finding and correlate optical coordinates with the physical coordinates in a mass spectrometer. Since most of the functionality of microMS is decoupled from the mass spectrometer, the workflow can be easily extended to a variety of instruments. Using matrix-assisted laser desorption/ionization (MALDI) time of flight (TOF)-MS, rodent pancreatic islet cells were investigated and heterogeneous peptide processing was detected at the single cell level. With secondary ion mass spectrometry, disparate tissue from the mammalian nervous system was differentiated and further stratified into separate populations. A unique feature of such analyses is that only a fraction of the sample is consumed and the location of a cell is constant once the sample is dried. This property greatly simplifies sequential, follow-up analysis. As an example, MALDI-TOF-MS was utilized to rapidly screen a population of islet cells to select alpha and beta cell types. The locations of those cells were then targeted for liquid microjunction extraction in order to examine their metabolite profiles with capillary electrophoresis-MS. Finally, while microscopy-guided MS profiling is accurate enough to target single cells, the methodology is flexible enough to analyze much larger samples, including tissue sections or bacterial colonies. As an application, natural product mutant libraries were screened directly from E. coli colonies using microMS. The suite of technologies and protocols described increases the applicability of many mass spectrometers to characterize a range of cells, colonies and similar objects for their chemical composition.
Issue Date:2017-04-19
Type:Thesis
URI:http://hdl.handle.net/2142/97602
Rights Information:Copyright 2017 Troy Comi
Date Available in IDEALS:2017-08-10
Date Deposited:2017-05


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