Quantitative Cryogenic Orbitrap Secondary Ion Mass Spectrometry for structural characterization of lipid nanoparticles

Lipid nanoparticles (LNPs) have shown high therapeutic utility as delivery vehicles for RNA, however, the way in which LNP chemical composition affects functional mRNA delivery is not completely understood.Surface and interface molecular analysis of LNPs can provide improved structure-function relationship information relevant to potency and tissue tropism in vivo, but there are limited techniques available to achieve the required interfacial characterisation.Secondary ion mass spectrometry (SIMS) has shown great potential for stratifying the lipid component of LNPs, with a prior study using qualitative depth profiles to confirm the basic structural arrangement of polyethylene glycol (PEG) lipids and RNA.This paper describes the first application of Quantitative cryogenic orbitrap secondary ion mass spectrometry (Q-Cryo-OrbiSIMS) to model the four canonical lipid components of LNPs, using quantified ion intensity profiles to plot the composition with depth.A combinatorial spot-in-spot mixing of the four lipid components generated 337 spots as a micro array on a glass slide.OrbiSIMS data is acquired from each spot.A variety of data pre-processing approaches are compared to scale the secondary ion intensity to minimise the effects of noise bias before construction of a calibration model.An artificial neural network model used to predict the four lipid compositions from the ion intensities produces a mean absolute error (MAE) of 14 %.The model is then used to predict quantitative molecular distributions from the OrbiSIMS profiles of cryogenically preserved LNPs.This demonstrates the feasibility of Q-Cryo-OrbiSIMS for LNPs, as well as the potential of this method for wider application to organic systems when suitable calibrant samples are available.