Spatial quantitative metabolomics enables identification of remote and sustained ipsilateral cortical metabolic reprogramming after stroke

Abstract

Mass spectrometry imaging (MSI) has become a cornerstone of spatial biology research. However, various factors that are intrinsic to the technology limit quantitative capacity of MSI-based spatial metabolomics and thus reliable interpretation. Here, we developed a quantitative MSI workflow (Q-MSI), based on isotopically 13C-labeled yeast extract as internal standards, to overcome these pitfalls. Using brain and kidney tissue, we demonstrate that this approach allows for (absolute) quantification of hundreds of metabolites and lipids. Applying our workflow to a stroke model allowed us to not only map metabolic remodeling of the infarct and peri-infarct area over time, but also discover hitherto unnoted remote metabolic remodeling in the histologically unaffected ipsilateral sensorimotor cortex. At day 7 post-stroke, increased levels of neuroprotective lysine and reduced excitatory glutamate levels were found compared to the contralateral cortex. By day 28 post-stroke, lysine and glutamate levels had been normalized, while decreased precursor pools of UDP-GlcNAc and linoleate persisted that have previously been associated with vulnerability. Importantly, traditional normalization strategies not employing internal standards were unable to visualize these differences. Using 13C-labeled yeast extracts as a normalization strategy establishes a new paradigm in quantitative MSI-based spatial metabolomics that greatly enhances reliability and interpretive strength.