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Spatial top-down proteomics for the functional characterization of human kidney.

Kevin J ZemaitisJames M FulcherRashmi KumarDavid J DegnanLogan A LewisYen-Chen LiaoMarija VeličkovićSarah M WilliamsRonald J MooreLisa M BramerDušan VeličkovićYing ZhuMowei ZhouLjiljana Pasa-Tolic
Published in: bioRxiv : the preprint server for biology (2024)
We developed an integrated workflow to directly identify proteoforms and reveal their spatial distributions. Where of the 20 differentially abundant proteoforms identified as discriminate between tubules and glomeruli by microPOTS, the vast majority of tubular proteoforms were of mitochondrial origin (8 of 10) where discriminate proteoforms in glomeruli were primarily hemoglobin subunits (9 of 10). These trends were also identified within ion images demonstrating spatially resolved characterization of proteoforms that has the potential to reshape discovery-based proteomics because the proteoforms are the ultimate effector of cellular functions. Applications of this technology have the potential to unravel etiology and pathophysiology of disease states, informing on biologically active proteoforms, which remodel the proteomic landscape in chronic and acute disorders.
Keyphrases
  • mass spectrometry
  • oxidative stress
  • liver failure
  • deep learning
  • single cell
  • machine learning
  • genome wide
  • high throughput
  • human health
  • climate change
  • hepatitis b virus
  • monte carlo