High-Throughput Single Cell Analysis and Molecular Imaging by Laser Ablation Electrospray Ionization Mass Spectrometry with Ion Mobility Separation

Metabolites, as a final downstream product of gene expression, are the ultimate actors in cellular processes. They represent the physiological state of the organism, its response to external or internal perturbations, and disease processes. The study of changes in metabolite composition and active metabolic pathways within complex biological samples requires ultra-sensitive analytical platforms with high-fidelity sample manipulation and rapid analysis. Mass spectrometry (MS)-based techniques are gaining ground in metabolomics due to their high sensitivity, broad molecular coverage, and quantitation capabilities. Among multiple ambient ionization techniques developed for in situ analysis of biological samples, laser ablation electrospray ionization (LAESI) stands out owing to low detection limits, minimal need for sample preparation, and imaging capabilities. This dissertation describes recent development and applications of the LAESI MS platform, developed for remote and high-throughput metabolomics of biological samples, including single cells, and for molecular imaging of organic molecules in hard tissues originating from environmental exposure. Chapter 1 of this dissertation presents the application of MS in metabolomics of volume limited samples with an emphasis on method development. It discusses the opportunities and challenges in single-cell measurements and introduces recent advances in ambient MS techniques used for remote molecular profiling and imaging of biological specimens. Chapter 2 describes the development of a fully automated optical fiber-based LAESI ionization source (f-LAESI) with significant improvement in sampling rate (~13 times higher than the previous configuration), used for the characterization of metabolic heterogeneity in soybean (Glycine max) root nodule cells infected by nitrogen-fixing soil bacteria (Bradyrhizobium japonicum). A more precise understanding of variations in cellular metabolism was achieved through the determination of metabolic noise values and the shape of metabolite abundance distributions for n > 1000 cells. To overcome the limitations in molecular coverage associated with limited sample size, traveling wave ion mobility separation (TW-IMS) was utilized on a millisecond timescale. It helped to distinguish structural isomers, reduce ion suppression effects, and enhance the signal-to-noise ratio, resulting in a two-times higher molecular coverage. Chapter 3 demonstrates the advantages of a remote ablation chamber with coaxial ablation axis and carrier gas flow for LAESI ionization for non-proximate MS analysis of samples in their native state. Using computational fluid dynamics (CFD), enhanced transfer efficiencies of both large (> 7.5 µm) and smaller particulates (< 6.5 µm) were calculated. Improved analytical figures of the redesigned ablation chamber included lower limits of detection and wide dynamic range. Chapter 4 demonstrates the application of two novel ionization platforms, LAESI and laser desorption ionization (LDI) from silicon nanopost array (NAPA), in the detection and molecular imaging of organic biomarkers in hard tissues, i.e., tooth dentine and scalp hair strands exposed to tobacco smoke. The detection of nicotine and its metabolites along with endogenous steroid hormones and lipid species was demonstrated. These findings were compared to results from matrix-assisted laser desorption ionization (MALDI) MS for the complementarity of their molecular coverage. Chapter 5 summarizes the work presented in this dissertation and provides future directions with respect to the application of soft ionization techniques for MS including the LAESI source in remote and high throughput MSI of metabolites and xenobiotics in complex biological specimens, including single cells. Applications of laser-based sampling and ionization methods for exposomic investigations are demonstrated through the local MS analysis and MSI of hard tissue (tooth and hair) samples. Potential strategies are discussed to improve the identification of metabolites, via, e.g., the separation of structural isomers based on advanced IMS.

Author

• Dolatmoradi, Marjan

Language

• English

Date created

• 2024

Type of Work

• Dissertation

License

• All rights reserved

Rights statement

• In Copyright

GW Unit

• Chemistry

Degree

• Ph.D.

Advisor

• Vertes, Akos

Committee Member(s)

• Miller, Houston
• Hao, Ling

Persistent URL

•  https://scholarspace.library.gwu.edu/etd/vq27zp29d