Campus Units

Chemistry, Ames Laboratory

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

2015

Journal or Book Title

Analyst

Volume

140

Issue

21

First Page

7293

Last Page

7304

DOI

10.1039/C5AN01079A

Abstract

Mass spectrometry imaging (MSI) provides high spatial resolution information that is unprecedented in traditional metabolomics analyses; however, the molecular coverage is often limited to a handful of compounds and is insufficient to understand overall metabolomic changes of a biological system. Here, we propose an MSI methodology to increase the diversity of chemical compounds that can be imaged and identified, in order to eventually perform untargeted metabolomic analysis using MSI. In this approach, we use the desorption/ionization bias of various matrixes for different metabolite classes along with dual polarities and a tandem MSI strategy. The use of multiple matrixes and dual polarities allows us to visualize various classes of compounds, while data-dependent MS/MS spectra acquired in the same MSI scans allow us to identify the compounds directly on the tissue. In a proof of concept application to a germinated corn seed, a total of 166 unique ions were determined to have high-quality MS/MS spectra, without counting structural isomers, of which 52 were identified as unique compounds. According to an estimation based on precursor MSI datasets, we expect over five hundred metabolites could be potentially identified and visualized once all experimental conditions are optimized and an MS/MS library is available. Lastly, metabolites involved in the glycolysis pathway and tricarboxylic acid cycle were imaged to demonstrate the potential of this technology to better understand metabolic biology.

Comments

This is a manuscript of an article from Analyst 140 (2015): 7293, doi: 10.1039/C5AN01079A. Posted with permission.

Copyright Owner

Royal Society of Chemistry

Language

en

File Format

application/pdf

Published Version

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