# Imaging Mass Spectrometry for metabolome mapping

> **NIH NIH R01** · BAYLOR COLLEGE OF MEDICINE · 2020 · $209,619

## Abstract

SUMMARY
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.

## Key facts

- **NIH application ID:** 10175695
- **Project number:** 3R01GM120033-04S1
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Zhandong Liu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $209,619
- **Award type:** 3
- **Project period:** 2017-01-01 → 2021-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10175695

## Citation

> US National Institutes of Health, RePORTER application 10175695, Imaging Mass Spectrometry for metabolome mapping (3R01GM120033-04S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10175695. Licensed CC0.

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