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Queries of MALDI-Imaging Global Datasets Identifying Ion Mass Signatures Associated with Tissue Compartments

Fehniger, Thomas LU ; Suits, Frank; Végvári, Ákos LU ; Horvatovich, Peter; Foster, Martyn and Marko-Varga, György LU (2014) In Proteomics 14(7-8). p.862-871
Abstract
Scanning mass spectrometry by matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) creates large volumetric global datasets that describe the location and identity of ions registered at each sampling location. While thousands of ion peaks are recorded in a typical whole tissue analysis, only a fraction of these measured molecules are purposefully scrutinized within a given experimental design. To address this need, we recently reported new methods to query the full volume of MALDI-MSI data that correlate all ion masses to one another. As an example of this utility we demonstrate that specific ion peak m/z signatures can be used to localize similar histological structures within tissue samples. In this study we... (More)
Scanning mass spectrometry by matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) creates large volumetric global datasets that describe the location and identity of ions registered at each sampling location. While thousands of ion peaks are recorded in a typical whole tissue analysis, only a fraction of these measured molecules are purposefully scrutinized within a given experimental design. To address this need, we recently reported new methods to query the full volume of MALDI-MSI data that correlate all ion masses to one another. As an example of this utility we demonstrate that specific ion peak m/z signatures can be used to localize similar histological structures within tissue samples. In this study we use the example of ion peak masses that are associated with tissue spaces occupied by airway bronchioles in rat lung samples. The volume of raw data was pre-processed into structures of 0.1 mass unit bins containing metadata collected at each sampling position. Interactive visualization in Paraview identified ion peaks that especially showed strong association with airway bronchioles but not vascular or parenchymal tissue compartments. Further iterative statistical correlation queries provided ranked indices of all m/z values in the global dataset regarding co-incident distributions at any given X,Y position in the histological spaces occupied by bronchioles The study further provides methods for extracting important information contained in global datasets that previously was unseen or inaccessible. This article is protected by copyright. All rights reserved. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Proteomics
volume
14
issue
7-8
pages
862 - 871
publisher
John Wiley & Sons
external identifiers
  • pmid:24478260
  • wos:000333691400008
  • scopus:84897423284
ISSN
1615-9861
DOI
10.1002/pmic.201300431
language
English
LU publication?
yes
id
63039d99-df01-4a10-b9e5-5f1d84fcf163 (old id 4286544)
date added to LUP
2014-02-13 09:27:45
date last changed
2017-01-01 03:14:25
@article{63039d99-df01-4a10-b9e5-5f1d84fcf163,
  abstract     = {Scanning mass spectrometry by matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) creates large volumetric global datasets that describe the location and identity of ions registered at each sampling location. While thousands of ion peaks are recorded in a typical whole tissue analysis, only a fraction of these measured molecules are purposefully scrutinized within a given experimental design. To address this need, we recently reported new methods to query the full volume of MALDI-MSI data that correlate all ion masses to one another. As an example of this utility we demonstrate that specific ion peak m/z signatures can be used to localize similar histological structures within tissue samples. In this study we use the example of ion peak masses that are associated with tissue spaces occupied by airway bronchioles in rat lung samples. The volume of raw data was pre-processed into structures of 0.1 mass unit bins containing metadata collected at each sampling position. Interactive visualization in Paraview identified ion peaks that especially showed strong association with airway bronchioles but not vascular or parenchymal tissue compartments. Further iterative statistical correlation queries provided ranked indices of all m/z values in the global dataset regarding co-incident distributions at any given X,Y position in the histological spaces occupied by bronchioles The study further provides methods for extracting important information contained in global datasets that previously was unseen or inaccessible. This article is protected by copyright. All rights reserved.},
  author       = {Fehniger, Thomas and Suits, Frank and Végvári, Ákos and Horvatovich, Peter and Foster, Martyn and Marko-Varga, György},
  issn         = {1615-9861},
  language     = {eng},
  number       = {7-8},
  pages        = {862--871},
  publisher    = {John Wiley & Sons},
  series       = {Proteomics},
  title        = {Queries of MALDI-Imaging Global Datasets Identifying Ion Mass Signatures Associated with Tissue Compartments},
  url          = {http://dx.doi.org/10.1002/pmic.201300431},
  volume       = {14},
  year         = {2014},
}