Metabolite mapping by consecutive nanostructure and silver-assisted mass spectrometry imaging on tissue sections

O J R Gustafsson, T M Guinan, D Rudd, H Kobus, K Benkendorff, N H Voelcker

Research output: Contribution to journalArticleResearchpeer-review

9 Citations (Scopus)

Abstract

RATIONALE: Nanostructure-based mass spectrometry imaging (MSI) is a promising technology for molecular imaging of small molecules, without the complex chemical background typically encountered in matrix-assisted molecular imaging approaches.Here, we have enhanced these surfaces with silver (Ag) to provide a second tier of MSI data from a single sample.
METHODS: MSI data was acquired through the application of laser desorption/ionization mass spectrometry to biological samples imprinted onto desorption/ionisation on silicon (DIOS) substrates. Following initial analysis, ultra-thin Ag layers were overlaid onto the samples followed by MSI analysis (Ag-DIOS MSI). This approach was first demonstrated for fingermark small molecules including environmental contaminants and sebum components. Subsequently, this bimodal method was translated to lipids and metabolites in fore-stomach sections from a 6-bromoisatin chemopreventative murine mouse model.
RESULTS: DIOS MSI allowed mapping of common ions in fingermarks as well as 6-bromoisatin metabolites and lipids in murine fore-stomach. Furthermore, DIOS MSI was complemented by the the Ag-DIOS MSI of Ag-adductable lipids such as wax esters in fingermarks and cholesterol in murine forestomach. Gastrointestinal acid condensation products of 6-bromoisatin, such as the 6,6’-dibromoindirubin mapped herein, are very challenging to isolate and characterize. By re-analysing the same tissue imprints,this metabolite was readily detected by DIOS, placed in a tissue-specific spatial context, and subsequently overlaid with additional lipid distributions acquired using Ag-DIOS MSI.
CONCLUSIONS: The ability to place metabolite and lipid classes in a tissue-specific context makes this novel method suited to MSI analyses where the collection of additional information from the same sample maximises resource use,and also maximises the number of annotated small molecules, in particular for metabolites that are typically undetectable with traditional platforms.
Original languageEnglish
Pages (from-to)991-1000
Number of pages15
JournalRapid Communications in Mass Spectrometry
Volume31
Issue number12
DOIs
Publication statusPublished - 30 Jun 2017

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