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MRI-compatible pipeline for three-dimensional MALDI imaging mass spectrometry using PAXgene fixation

: Oetjen, J.; Aichler, M.; Trede, D.; Strehlow, J.; Berger, J.; Heldmann, S.; Becker, M.; Gottschalk, M.; Kobarg, J.H.; Wirtz, S.; Schiffler, S.; Thiele, H.; Walch, A.; Maass, P.; Alexandrov, T.


Journal of Proteomics 90 (2013), pp.52-60
ISSN: 1874-3919
ISSN: 1876-7737
Siena Meeting "From Genome to Proteome - Open Innovations" <9, 2012, Siena>
Journal Article, Conference Paper
Fraunhofer MEVIS ()

MALDI imaging mass spectrometry (MALDI-imaging) has emerged as a spatially-resolved label-free bioanalytical technique for direct analysis of biological samples and was recently introduced for analysis of 3D tissue specimens. We present a new experimental and computational pipeline for molecular analysis of tissue specimens which integrates 3D MALDI-imaging, magnetic resonance imaging (MRI), and histological staining and microscopy, and evaluate the pipeline by applying it to analysis of a mouse kidney. To ensure sample integrity and reproducible sectioning, we utilized the PAXgene fixation and paraffin embedding and proved its compatibility with MRI. Altogether, 122 serial sections of the kidney were analyzed using MALDI-imaging, resulting in a 3D dataset of 200 GB comprised of 2 million spectra. We show that elastic image registration better compensates for local distortions of tissue sections. The computational analysis of 3D MALDI-imaging data was performed using ou r spatial segmentation pipeline which determines regions of distinct molecular composition and finds m/z-values co-localized with these regions. For facilitated interpretation of 3D distribution of ions, we evaluated isosurfaces providing simplified visualization. We present the data in a multimodal fashion combining 3D MALDI-imaging with the MRI volume rendering and with light microscopic images of histologically stained sections. Biological significance: Our novel experimental and computational pipeline for 3D MALDI-imaging can be applied to address clinical questions such as proteomic analysis of the tumor morphologic heterogeneity. Examining the protein distribution as well as the drug distribution throughout an entire tumor using our pipeline will facilitate understanding of the molecular mechanisms of carcinogenesis. This article is part of a Special Issue entitled: From Genome to Proteome: Open Innovations.