Title
More from less : high-throughput dual polarity lipid imaging of biological tissues
Author
Faculty/Department
Faculty of Pharmaceutical, Biomedical and Veterinary Sciences . Biomedical Sciences
Publication type
article
Publication
Cambridge ,
Subject
Chemistry
Biology
Human medicine
Source (journal)
The analyst. - Cambridge
Volume/pages
141(2016) :12 , p. 3832-3841
ISSN
0003-2654
ISI
000378942900037
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
The high ion signals produced by many lipids in mass spectrometry imaging (MSI) make them an ideal molecular class to study compositional changes throughout tissue sections and their relationship with disease. However, the large extent of structural diversity observed in the lipidome means optimal ion signal for different lipid classes is often obtained in opposite polarities. In this work we demonstrate how new high speed MALDI-MSI technologies combined with precise laser position control enables the acquisition of positive and negative ion mode lipid data from the same tissue section much faster than is possible with other MSI instruments. Critically, using this approach we explicitly demonstrate how such dual polarity acquisitions provide more information regarding molecular composition and spatial distributions throughout biological tissues. For example, in applying this approach to the zebra finch songbird brain we reveal the high abundance of DHA containing phospholipids (PC in positive mode and PE, PS in negative ion mode) in the nuclei that control song learning behaviour. To make the most of dual polarity data from single tissues we have also developed a pLSA-based multivariate analysis technique that includes both positive and negative ion data in the classification approach. In doing so the correlation amongst different lipid classes that ionise best in opposite polarities and contribute to certain spatial patterns within the tissue can be directly revealed. To demonstrate we apply this approach to studying the lipidomic changes throughout the tumor microenvironment within xenografts from a lung cancer model.
Full text (open access)
https://repository.uantwerpen.be/docman/irua/02c38b/132761_2017_01_23.pdf
E-info
https://repository.uantwerpen.be/docman/iruaauth/6dce99/134658.pdf
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