Raman-guided subcellular pharmaco-metabolomics for metastatic melanoma cells

Jiajun Du, Yapeng Su, Chenxi Qian, Dan Yuan, Kun Miao, Dongkwan Lee, Alphonsus H. C. Ng, Reto S. Wijker, Antoni Ribas, Raphael D. Levine, James R. Heath () and Lu Wei ()
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Jiajun Du: California Institute of Technology
Yapeng Su: California Institute of Technology
Chenxi Qian: California Institute of Technology
Dan Yuan: Institute for Systems Biology
Kun Miao: California Institute of Technology
Dongkwan Lee: California Institute of Technology
Alphonsus H. C. Ng: Institute for Systems Biology
Reto S. Wijker: California Institute of Technology
Antoni Ribas: University of California Los Angeles
Raphael D. Levine: University of California Los Angeles
James R. Heath: Institute for Systems Biology
Lu Wei: California Institute of Technology

Nature Communications, 2020, vol. 11, issue 1, 1-16

Abstract: Abstract Non-invasively probing metabolites within single live cells is highly desired but challenging. Here we utilize Raman spectro-microscopy for spatial mapping of metabolites within single cells, with the specific goal of identifying druggable metabolic susceptibilities from a series of patient-derived melanoma cell lines. Each cell line represents a different characteristic level of cancer cell de-differentiation. First, with Raman spectroscopy, followed by stimulated Raman scattering (SRS) microscopy and transcriptomics analysis, we identify the fatty acid synthesis pathway as a druggable susceptibility for differentiated melanocytic cells. We then utilize hyperspectral-SRS imaging of intracellular lipid droplets to identify a previously unknown susceptibility of lipid mono-unsaturation within de-differentiated mesenchymal cells with innate resistance to BRAF inhibition. Drugging this target leads to cellular apoptosis accompanied by the formation of phase-separated intracellular membrane domains. The integration of subcellular Raman spectro-microscopy with lipidomics and transcriptomics suggests possible lipid regulatory mechanisms underlying this pharmacological treatment. Our method should provide a general approach in spatially-resolved single cell metabolomics studies.

Date: 2020
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DOI: 10.1038/s41467-020-18376-x

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