Going Beyond Images: Exploration of Hormone Processing Pathways in Diabetic Mouse Models via Mass Spectral Imaging and Data-mining

摘要

Mass spectral imaging (MSI) allows for high throughput screening of the localization of hundreds of biomolecules in tissue. However, little attention has been paid to the development of approaches that examine co-localization and correlated expression between these molecules. In this work we demonstrate that the combination of mass spectral imaging technology with an appropriate in silico data-mining strategy unlocks an intrinsic potential of MSI. It generates a powerful analytical technology for screening major biochemical processes in tissue rather than tracking solitary ions. The potential of the approach is demonstrated in a diabetes context by using the method to differentially analyze metabolic pathways between different diabetes mouse models.