Adapting expansion microscopy to imaging mass spectrometry : multiplexed interrogation of pathology samples at high resolution

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The recent development of Expansion Microscopy (ExM) and related techniques physically enlarge samples for enhanced spatial resolution while largely retaining native biomolecular content and coordinates, but almost exclusive to fluorescent imaging as the readout modality, which restricts its multiplex ability, and the range of biomolecule targets that can be studied. In contrast, Imaging Mass Spectrometry (IMS) has emerged as a powerful tool for acquiring spatially multiplexed or omics information, particularly in the label-free profiling of biomolecule targets. IMS excels at investigating cellular positioning in tissues but currently faces challenges in achieving high-resolution biomolecular features due to costly instrumental modifications and limitations imposed by physics. Integrating ExM with tissue IMS technologies would enable comprehensive and multiscale studies of tissue biology. While this concept seems straightforward, it is counterintuitive since the expanded ExM hydrogel resembles a sponge filled with water, whereas most IMS methodologies typically require water-free samples for optimal resolution and to meet sample handling requirements. This dissertation proposes an ExM framework that not only enables complete removal of water from hydrogels while preserving their lateral magnification, but also preserves the biomolecules inside expanded archival clinical samples. The processed hydrogel can be seamlessly integrated into existing tissue staining protocols and IMS instrumentation with minimal modifications. By combining the strengths of ExM and IMS, this research opens up new possibilities for investigating tissue biology at multiple scales, facilitating a deeper understanding of complex biological systems. Chapter 1 provides an overview of the methodology background and concepts, along with the motivation of this thesis work. I start with the introduction of the current stage of ExM, with a inspection of two mainstream workflows of ExM, and the underlying principle of the expansion process. The chapter then delves into the current stage of IMS, encompassing both Secondary Ion Mass Spectrometer-IMS (SIMS-IMS) and Matrix Assisted Laser Desorption/Ionization-IMS (MALDI-IMS) is introduced. This comprehensive picture will set the stage for discussing the motivation behind this thesis work, focusing on the limitations that could been overcome and the possibilities that have emerged with the advent of the ExM hydrogel platform to other imaging modalities, particularly IMS. Then, an close inspection on the obstacles, the fragility and high-water content of the fully expanded ExM hydrogel is introduced. Chapter 2 provides detailed insights into the selection and optimization of protocols to combine ExM with antibody mass-tag reporters and SIMS-based multiplex imaging methods such as Multiplexed Ion Beam Imaging (MIBI) and Imaging Mass Cytometry (IMC). This chapter presents a solution to address the challenges posed by the fragility and high-water content of the fully expanded ExM hydrogel. A controlled dehydration protocol with substrate adhesion is introduced for fully expanded samples to facilitate the formation of vacuum-compatible hydrogels for IMS instruments. Distortion test, thickness measurement and expansion fold assessment are performed to characterize the hydrogel. Thus, the chapter establishes a pipeline that allows archival human tissue sections to be expanded to 3.7 times of their original size, stained with Lanthanide-conjugated antibody cocktails, completely dehydrated to be accommodated in vacuum or desiccated chambers of IMS instruments, then imaged by MIBI or IMC using the same parameters as normal tissue sections, which I termed as Expand and comPRESS hydrOgels (ExPRESSO). This pipeline has been applied to archival human lymphoid and brain tissue sections to resolve orchestrated features of tissue architecture, particularly that of the Blood-Brain Barrier (BBB). With further antibody titration, this pipeline holds promise to interrogate archival tissue section with more than 40 channels down to 100 nm resolution for deep tissue profiling. In addition, this pipeline has been extended to include nucleotide targets, allowing for genus-level differentiation of mouse gut bacteria and their interaction with host cells. Chapter 3 further explores the possibility of combining ExPRESSO and label-free IMS imaging methodology, e.g. MALDI-IMS. With ExPRESSO, the majority of proteomics and associated N-Glycans can be anchored and expanded up to 4 times of its original size, and adapted to MALDI-IMS as a readout modality. With a modified protocol that compatible with MALDI-IMS, this chapter demonstrates that N-Glycan signals can be preserved through the ExPRESSO protocol, then be profiled with MALDI-IMS with a enhanced resolution compared with non-expanded sample. These results pave the way for routine N-Glycans profiling of archival tissues at resolutions as high as the single-cell level, enabling deeper interrogation and understanding of heterogeneity of pathological states in humans.


Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2023; ©2023
Publication date 2023; 2023
Issuance monographic
Language English


Author Bai, Yunhao
Degree supervisor Nolan, Garry P
Thesis advisor Nolan, Garry P
Thesis advisor Boxer, Steven G. (Steven George), 1947-
Thesis advisor Waymouth, Robert M
Degree committee member Boxer, Steven G. (Steven George), 1947-
Degree committee member Waymouth, Robert M
Associated with Stanford University, School of Humanities and Sciences
Associated with Stanford University, Department of Chemistry


Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Yunhao Bai.
Note Submitted to the Department of Chemistry.
Thesis Thesis Ph.D. Stanford University 2023.

Access conditions

© 2023 by Yunhao Bai
This work is licensed under a Creative Commons Attribution Non Commercial Share Alike 3.0 Unported license (CC BY-NC-SA).

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