Advancing functional mass spectrometry imaging methodology to monitor dynamic physiological processes

North Carolina State University Raleigh, Raleigh NC

Investigators

Abstract

PROJECT SUMMARY Spatially resolved ‘omics techniques have been instrumental in describing the heterogeneity in molecular content in tissues. However, these methods can only provide static measures of the variation in content and fall short on relating how this molecular heterogeneity results in differences in tissue function. Our laboratories have developed a unique functional Mass Spectrometry Imaging (fMSI) method that can measure tissue perfusion and metabolic activities at high spatial resolution and can provide a critical link between spatially resolved ‘omics data and cellular phenotype. This fMSI method uses timed infusions of isotopologues of a single substrate prior to tissue harvest to obtain dynamic data at each sampled location. We demonstrated the feasibility of this method to detect uptake (perfusion) of isotopologues of glycine and their conversion to glutathione in liver and tumor tissue but there remain significant challenges to realizing the full potential of this method. This project is centered around four aims. Aim 1 will evaluate different bolus and constant infusions protocols for isotopologue administration with the objective to improve the sensitivity and extend the observable metabolic window. Aim 2 will administer isotopologues of pimonidazole and urea to demonstrate that fMSI can detect oxygenation and perfusion dynamics in tissues. Aim 3 will demonstrate the general utility of the fMSI method to measure pentose phosphate pathway activity in tissues. Aim 4 will tie together the fMSI data to generate spatially-specific mathematical models of tissue metabolism and validate in vivo observations of the effect of microenvironmental variations on metabolism using in vitro perfusion models. Successful completion of these Aims will position fMSI as a unique bioanalytical tool to provide high spatially resolved functional data in any tissue sample.