Microscopy-Directed Imaging Mass Spectrometry for Rapid High Spatial Resolution Molecular Imaging of Glomeruli

Esselman, Allison B.; Patterson, Nathan Heath; Migas, L.G.; Dufresne, Martin; Djambazova, Katerina V.; Colley, Madeline E.; Van de Plas, Raf; Spraggins, Jeffrey M.

doi:10.1021/jasms.3c00033

Microscopy-Directed Imaging Mass Spectrometry for Rapid High Spatial Resolution Molecular Imaging of Glomeruli

Journal article (2023)

Authors

Allison B. Esselman VanderBilt University

Nathan Heath Patterson VanderBilt University

L.G. Migas Team Raf Van de Plas - Mechanical, Maritime and Materials Engineering , VanderBilt University

Martin Dufresne VanderBilt University

Katerina V. Djambazova VanderBilt University

Madeline E. Colley VanderBilt University

Raf Van de Plas Team Raf Van de Plas - Mechanical, Maritime and Materials Engineering , VanderBilt University

Jeffrey M. Spraggins VanderBilt University

Research Group

Team Raf Van de Plas (Mechanical, Maritime and Materials Engineering) (TU Delft)

DOI: https://doi.org/10.1021/jasms.3c00033

Multimodal Molecular imaging High-throughput Targeted Lipids Glomeruli High spatial resolution imaging Human kidney MALDI IMS Unsupervised machine learning Whole slide imaging

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Published Date

2023

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Raf Van de Plas

Abstract

The glomerulus is a multicellular functional tissue unit (FTU) of the nephron that is responsible for blood filtration. Each glomerulus contains multiple substructures and cell types that are crucial for their function. To understand normal aging and disease in kidneys, methods for high spatial resolution molecular imaging within these FTUs across whole slide images is required. Here we demonstrate a workflow using microscopy-driven selected sampling to enable 5 μm pixel size matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) of all glomeruli within whole slide human kidney tissues. Such high spatial resolution imaging entails large numbers of pixels, increasing the data acquisition times. Automating FTU-specific tissue sampling enables high-resolution analysis of critical tissue structures, while concurrently maintaining throughput. Glomeruli were automatically segmented using coregistered autofluorescence microscopy data, and these segmentations were translated into MALDI IMS measurement regions. This allowed high-throughput acquisition of 268 glomeruli from a single whole slide human kidney tissue section. Unsupervised machine learning methods were used to discover molecular profiles of glomerular subregions and differentiate between healthy and diseased glomeruli. Average spectra for each glomerulus were analyzed using Uniform Manifold Approximation and Projection (UMAP) and k-means clustering, yielding 7 distinct groups of differentiated healthy and diseased glomeruli. Pixel-wise k-means clustering was applied to all glomeruli, showing unique molecular profiles localized to subregions within each glomerulus. Automated microscopy-driven, FTU-targeted acquisition for high spatial resolution molecular imaging maintains high-throughput and enables rapid assessment of whole slide images at cellular resolution and identification of tissue features associated with normal aging and disease.

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