Drugs that influence enzymes of lipid metabolism can cause pathological accumulation of lipids in animal cells. Here, gold nanoparticles, acting as nanosensors that deliver surface-enhanced Raman scattering (SERS) spectra from living cells provide molecular evidence of lipid accumulation in lysosomes after treatment of cultured cells with the three tricyclic antidepressants (TCA) desipramine, amitryptiline, and imipramine. The vibrational spectra elucidate to great detail and with very high sensitivity the composition of the drug-induced lipid accumulations, also observed in fixed samples by electron microscopy and X-ray nanotomography. The nanoprobes show that mostly sphingomyelin is accumulated in the lysosomes but also other lipids, in particular, cholesterol. The observation of sphingomyelin accumulation supports the impairment of the enzyme acid sphingomyelinase. The SERS data were analyzed by random forest based approaches, in particular, by minimal depth variable selection and surrogate minimal depth (SMD), shown here to be particularly useful machine learning tools for the analysis of the lipid signals that contribute only weakly to SERS spectra of cells. SMD is used for the identification of molecular colocalization and interactions of the drug molecules with lipid membranes and for discriminating between the biochemical effects of the three different TCA molecules, in agreement with their different activity. The spectra also indicate that the protein composition is significantly changed in cells treated with the drugs.
Keywords: SERS; gold nanoparticles; lipid accumulation; lipidosis; random forest; sphingomyelin; tricyclic antidepressants.