Microscopy-Directed Imaging Mass Spectrometry for Rapid High Spatial Resolution Molecular Imaging of Glomeruli
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https://figshare.com/articles/dataset/Microscopy-Directed_Imaging_Mass_Spectrometry_for_Rapid_High_Spatial_Resolution_Molecular_Imaging_of_Glomeruli/23527842
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资源简介:
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.
创建时间:
2023-06-15



