4.8 Article

Spatial Metabolomics of the Human Kidney using MALDI Trapped Ion Mobility Imaging Mass Spectrometry

期刊

ANALYTICAL CHEMISTRY
卷 92, 期 19, 页码 13084-13091

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.0c02051

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资金

  1. NIH Common Fund
  2. National Institute of Diabetes and Digestive and Kidney Diseases [U54DK120058]
  3. NIH National Institute of Allergy and Infectious Disease [R01 AI138581]
  4. National Science Foundation Major Research Instrument Program [CBET-1828299]
  5. NIH National Institute of General Medical Sciences [2P41GM103391]
  6. National Institute of Environmental Health Sciences [T32ES007028]
  7. NIH National Cancer Institute [5 UM1 CA183727-08]

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Low molecular weight metabolites are essential for defining the molecular phenotypes of cells. However, spatial metabolomics tools often lack the sensitivity, specify, and spatial resolution to provide comprehensive descriptions of these species in tissue. MALDI imaging mass spectrometry (IMS) of low molecular weight ions is particularly challenging as MALDI matrix clusters are often nominally isobaric with multiple metabolite ions, requiring high resolving power instrumentation or derivatization to circumvent this issue. An alternative to this is to perform ion mobility separation before ion detection, enabling the visualization of metabolites without the interference of matrix ions. Additional difficulties surrounding low weight metabolite visualization include high resolution imaging, while maintaining sufficient ion numbers for broad and representative analysis of the tissue chemical complement. Here, we use MALDI timsTOF IMS to image low molecular weight metabolites at higher spatial resolution than most metabolite MALDI IMS experiments (20 mu m) while maintaining broad coverage within the human kidney. We demonstrate that trapped ion mobility spectrometry (TIMS) can resolve matrix peaks from metabolite signal and separate both isobaric and isomeric metabolites with different distributions within the kidney. The added ion mobility data dimension dramatically increased the peak capacity for spatial metabolomics experiments. Through this improved sensitivity, we have found >40 low molecular weight metabolites in human kidney tissue, such as argininic acid, acetylcarnitine, and choline that localize to the cortex, medulla, and renal pelvis, respectively. Future work will involve further exploring metabolomic profiles of human kidneys as a function of age, sex, and race.

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