STILL-13C: Spatial tracing of isotopically labelled lipids with 13C reveals metabolic heterogeneity in intact tissues
Lipid metabolism is dynamically rewired across tissues in response to developmental, environmental and therapeutic cues. This adaptation drives treatment resistance in a range of human pathologies, but current lipidomic techniques fail to capture the underlying mechanisms, relying on steady-state measurements from homogenised samples that obscure spatial heterogeneity and pathway flux. Here we…
Lipid metabolism exhibits dynamic adaptation across tissues in response to various factors such as development, environment, and therapy. However, conventional lipidomic techniques struggle to capture this spatial heterogeneity and pathway flux due to their reliance on steady-state measurements from homogenized samples. To address this issue, researchers have developed a novel approach called Spatial Tracing of Isotopically Labeled Lipids (STILL-13C).
This workflow combines stable isotope tracing with high-resolution mass spectrometry imaging (MSI) to directly map lipid metabolic flux within intact human tissues, offering an unprecedented level of pathway coverage.
The STILL-13C method effectively overcomes the limitations of bulk and MSI-based analyses by spatially resolving isotopologue labeling of both simple and complex lipids. This enables simultaneous tracing of fatty acid synthesis, lipid remodeling, and multiple convergent pathways involved in phospholipid assembly, all while maintaining the tissue's original architecture and regional metabolic context.
In a study conducted on patient-derived prostate cancer explants cultured ex vivo, the STILL-13C technique revealed significant heterogeneity in lipid pathway activity between neighboring epithelial regions. It also demonstrated spatially resolved responses to pathway inhibition.
By establishing a broadly applicable platform for investigating spatial heterogeneity in lipid metabolic flux and its perturbation in intact tissues, the STILL-13C approach promises to significantly enhance our understanding of the complex dynamics underlying lipid metabolism in various human pathologies.
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