Multiscale MALDI mass spectrometry for tissue, cellular, and subcellular lipidomics

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) has revolutionized bioanalytical chemistry by enabling spatially resolved molecular analysis across biological scales, from whole tissues to single cells and subcellular organelles. The ability to perform high-throughput, label-free analysis of complex biological samples has positioned MALDI-MS as a critical tool in biomedical and biochemical research. However, significant challenges remain in extending its capabilities to deeper levels of cellular resolution, particularly in detecting and characterizing individual organelles. This dissertation focuses on the advancement and application of MALDI-MS for multiscale lipidomic analysis, pushing the limits of possible applications to explore lipid heterogeneity in tissues, single cells, and isolated organelles. At the tissue level, MALDI mass spectrometry imaging (MSI) enables spatial mapping of molecular distributions, providing valuable insights into the biochemical landscape of biological systems. This technique has been widely applied in disease pathology, drug metabolism studies, and biomarker discovery. Utilizing advanced instrumentation, such as a MALDI-2 timsTOF MS, we optimized lipid detection and enhance the sensitivity of molecular imaging approaches while also enabling more comprehensive analysis via gas-phase separation with trapped ion mobility. These advancements allow for improved characterization of lipidomic changes in response to drug treatments and metabolic alterations, contributing to a deeper understanding of biochemical processes at the tissue level. Expanding beyond bulk tissue analysis, this dissertation explores single-cell MALDI-MS, a powerful approach for capturing lipidomic variations at the level of individual cells. Cellular heterogeneity is a fundamental aspect of biology, influencing disease progression, therapeutic response, and metabolic regulation. Traditional bulk analyses often obscure these differences, averaging signals across diverse cell populations. By leveraging single-cell lipidomics, we can resolve metabolic differences between genetically distinct cells, diseased and healthy populations, and drug-treated versus untreated cells. Through instrumental optimization and methodological advancements, this work enhances the sensitivity and throughput of single-cell MALDI-MS, enabling the characterization of cell-type-specific lipid signatures and providing deeper insights into the biochemical diversity that drives cellular function and pathology. One of the more challenging aspects in targeted mass spectrometry is the extension of single-cell analysis to the subcellular level, particularly the detection and characterization of organelles. This work further advances our single-organelle MALDI-MS capabilities, specifically targeting isolated mammalian mitochondria as a model system for lipidomic profiling. Mitochondria play a central role in energy metabolism, apoptosis, and disease progression, yet their lipid composition remains difficult to study due to their small size and low analyte concentrations. By leveraging optimized MALDI approaches, we demonstrate the feasibility of direct lipid analysis of individual mitochondria. Through the development and application of MALDI-MS techniques across multiple scales, this dissertation provides a framework for multiscale lipidomic analysis, from tissue-wide imaging to subcellular organelle profiling. By advancing the sensitivity and specificity of MALDI-based techniques, we enable more precise investigations into lipid metabolism, disease mechanisms, and drug responses. These findings contribute to the growing field of mass spectrometry-based omics, expanding the potential of MALDI-MS for biomedical research, precision medicine, and metabolic engineering.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Chemistry

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Croslow, Seth W.

Contributors dc:contributor

• Sweedler, Jonathan V.
• Sweedler, Jonathan V
• Murphy, Catherine J
• Rodriguez-Lopez, Joaquin
• Shen, Mei

• Mass Spectrometry
• Maldi
• Lipidomics
• Single Cells
• Single Organelles
• Mass Spectrometry Imaging

Statement dc:rights

• Copyright 2025 Seth Croslow

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/129815

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F129815