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

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

Esselman, Allison B. (VanderBilt University)
Patterson, Nathan Heath (VanderBilt University)
Migas, L.G. (TU Delft Team Raf Van de Plas; VanderBilt University)
Dufresne, Martin (VanderBilt University)
Djambazova, Katerina V. (VanderBilt University)
Colley, Madeline E. (VanderBilt University)
Van de Plas, Raf (TU Delft Team Raf Van de Plas; VanderBilt University)
Spraggins, Jeffrey M. (VanderBilt University)

2023

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.

glomeruli
high spatial resolution imaging
high-throughput
human kidney
lipids
MALDI IMS
molecular imaging
multimodal
targeted
unsupervised machine learning
whole slide imaging

http://resolver.tudelft.nl/uuid:5d36e644-88a6-4350-9d93-02fd3e642bc0

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

2023-12-15

1044-0305

American Society for Mass Spectrometry. Journal, 34 (7), 1305-1314

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2023 Allison B. Esselman, Nathan Heath Patterson, L.G. Migas, Martin Dufresne, Katerina V. Djambazova, Madeline E. Colley, Raf Van de Plas, Jeffrey M. Spraggins