In response to NOT-GM-20-013, we are requesting a supplement to our R01 5R01GM120033-04 for an MALDI imaging source unit to be attached to an existing Q ExactiveMass Spectrometer (Ultra-High Mass Range Hybrid Quadrupole-Orbitrap?) for spatial mapping of metabolites in thin tissue sections. Within our R01 award, to analyze NMR metabolome data we are developing two novel, powerful, and automated algorithms that capitalize on recent developments in machine learning. We have coded these algorithms and tested their sensitivity and specificity on both synthesized and real data. We then applied these methods to human disease models and identified putative biomarkers. To validate these biomarkers, we have developed methods to analyze animal tissues and human brain organoids using imaging mass spectrometry (IMS), which permits spatial localization of metabolites without labeling. This targeted IMS metabolic phenotyping approach complements our untargeted NMR methods: it allows us to determine whether the individual metabolites identified by NMR represent bona fide biomarkers and to develop metabolic hypotheses for their association with disease. We submit this request for imaging mass spectrometer hardware because a nearby IMS facility on which we have relied has closed and no other IMS facility exists in greater Houston area. Performing the IMS studies ourselves, with the help of collaborators, will accelerate our discovery about the role small molecules and metabolites play in health and disease. This instrument will help us better i) perform metabolome screens to identify the effects of SARS-CoV-2 on neural cell types in human brain organoid models; ii) perform high-throughput drug screening to stimulate neural stem cells to produce new neurons in the brain organoid models to regenerate damaged tissue; and iii) use our NMR algorithms to develop a protocol for quantitative imaging. None of these studies will be possible without the imaging mass spectrometer. Given our access to state-of-the-art equipment, data-collection expertise, and new analytical algorithms that are especially sensitive and specific to NMR spectral data, we are uniquely positioned to advance biomarker and diagnostics tools and screening methods for metabolites and synthetic small molecules. Using an imaging mass spectrometer to map metabolite distribution may help us discover diagnostic and prognostic biomarkers not only for SARS-CoV-2, but for a broad spectrum of brain disorders that lead to neurodegeneration. Such broad usage of our platform would be transformative for neuroscientists, neurologists, and their patients.
The metabolome is a dynamic and sensitive biological system that reflects both innate processes and environmental influences, and can therefore tell us much about an organism's health and homeostasis. In our R01, we are developing two novel, powerful, and automated algorithms to analyze NMR metabolome data. We are requesting an MALDI imaging source unit to attach to an existing Q ExactiveMass Spectrometer (Ultra- High Mass Range Hybrid Quadrupole-Orbitrap?) to validate our ongoing NMR studies and accelerate the translation of our biomarker discoveries to the clinical realm.
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