Preclinical study demonstrates multiplexed in situ enzyme activity mapping across liver tumor models, highlighting a new framework for spatial enzymology.
Key Points
To develop a multiplexed, semi-quantitative imaging platform for mapping functional enzyme activities directly within intact tissue sections.
Synthesized a library of 31 mass-tagged substrates targeting proteases, kinases, histone acetyltransferases, and glycosyltransferases to allow simultaneous product detection.
Utilized a ratiometric product-to-substrate calculation to correct for tissue-dependent ionization bias during MALDI mass spectrometry imaging.
Evaluated spatial enzyme activity in zinc-fixed tissue sections from healthy mouse liver, a murine hepatocellular carcinoma model, and an ablated rabbit VX2 liver tumor model.
Generated spatially resolved multi-enzyme activity maps that delineated distinct functional zones between tumor and normal liver tissue.
Unsupervised clustering and dimensionality reduction via UMAP accurately reproduced anatomical and histological tissue patterns based purely on enzymatic activity readouts.