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Updated: Jul 8, 2026

Application of Laser Microdissection to Uncover Regional Transcriptomics in Human Kidney Tissue
Published on: June 9, 2020
Spatially resolved metabolomic dataset of distinct human kidney anatomic regions
Haikuo Li1, Benjamin D Humphreys1,2
1Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
Abstract:
Cortex, medulla and papilla are three major human kidney anatomic structures and they harbour unique metabolic functions, but the underlying metabolomic profiles are largely unknown at spatial resolution. Here, we generated a spatially resolved metabolomics dataset on human kidney cortex, medulla and papilla tissues dissected from the same donor. Matrix-Assisted Laser Desorption/Ionization-Imaging Mass Spectrometry (MALDI-IMS) was used to detect metabolite species over mass-to-charge ratios of 50 -1500 for each section at a resolution of 10 × 10 µm2 pixel size. We present raw data matrix of each sample, feature annotations, raw AnnData merged from three samples and processed AnnData files after quality control, dimensional reduction and data integration, which contains a total of 170,459 spatially resolved metabolomes with 562 features detected. This dataset can be either visualized through an interactive browser or further analyzed to study metabolomic heterogeneity across regional human kidney anatomy.
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