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Fourier Transform Infrared Microscopy Enables Guidance of Automated Mass Spectrometry Imaging to Predefined Tissue Morphologies
Multimodal imaging combines complementary platforms for spatially resolved tissue analysis that are poised for application in life science and personalized medicine. Unlike established clinical in vivo multimodality imaging, automated workflows for in-depth multimodal molecular ex vivo tissue analys...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5762902/ https://www.ncbi.nlm.nih.gov/pubmed/29321555 http://dx.doi.org/10.1038/s41598-017-18477-6 |
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author | Rabe, Jan-Hinrich A. Sammour, Denis Schulz, Sandra Munteanu, Bogdan Ott, Martina Ochs, Katharina Hohenberger, Peter Marx, Alexander Platten, Michael Opitz, Christiane A. Ory, Daniel S. Hopf, Carsten |
author_facet | Rabe, Jan-Hinrich A. Sammour, Denis Schulz, Sandra Munteanu, Bogdan Ott, Martina Ochs, Katharina Hohenberger, Peter Marx, Alexander Platten, Michael Opitz, Christiane A. Ory, Daniel S. Hopf, Carsten |
author_sort | Rabe, Jan-Hinrich |
collection | PubMed |
description | Multimodal imaging combines complementary platforms for spatially resolved tissue analysis that are poised for application in life science and personalized medicine. Unlike established clinical in vivo multimodality imaging, automated workflows for in-depth multimodal molecular ex vivo tissue analysis that combine the speed and ease of spectroscopic imaging with molecular details provided by mass spectrometry imaging (MSI) are lagging behind. Here, we present an integrated approach that utilizes non-destructive Fourier transform infrared (FTIR) microscopy and matrix assisted laser desorption/ionization (MALDI) MSI for analysing single-slide tissue specimen. We show that FTIR microscopy can automatically guide high-resolution MSI data acquisition and interpretation without requiring prior histopathological tissue annotation, thus circumventing potential human-annotation-bias while achieving >90% reductions of data load and acquisition time. We apply FTIR imaging as an upstream modality to improve accuracy of tissue-morphology detection and to retrieve diagnostic molecular signatures in an automated, unbiased and spatially aware manner. We show the general applicability of multimodal FTIR-guided MALDI-MSI by demonstrating precise tumor localization in mouse brain bearing glioma xenografts and in human primary gastrointestinal stromal tumors. Finally, the presented multimodal tissue analysis method allows for morphology-sensitive lipid signature retrieval from brains of mice suffering from lipidosis caused by Niemann-Pick type C disease. |
format | Online Article Text |
id | pubmed-5762902 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-57629022018-01-17 Fourier Transform Infrared Microscopy Enables Guidance of Automated Mass Spectrometry Imaging to Predefined Tissue Morphologies Rabe, Jan-Hinrich A. Sammour, Denis Schulz, Sandra Munteanu, Bogdan Ott, Martina Ochs, Katharina Hohenberger, Peter Marx, Alexander Platten, Michael Opitz, Christiane A. Ory, Daniel S. Hopf, Carsten Sci Rep Article Multimodal imaging combines complementary platforms for spatially resolved tissue analysis that are poised for application in life science and personalized medicine. Unlike established clinical in vivo multimodality imaging, automated workflows for in-depth multimodal molecular ex vivo tissue analysis that combine the speed and ease of spectroscopic imaging with molecular details provided by mass spectrometry imaging (MSI) are lagging behind. Here, we present an integrated approach that utilizes non-destructive Fourier transform infrared (FTIR) microscopy and matrix assisted laser desorption/ionization (MALDI) MSI for analysing single-slide tissue specimen. We show that FTIR microscopy can automatically guide high-resolution MSI data acquisition and interpretation without requiring prior histopathological tissue annotation, thus circumventing potential human-annotation-bias while achieving >90% reductions of data load and acquisition time. We apply FTIR imaging as an upstream modality to improve accuracy of tissue-morphology detection and to retrieve diagnostic molecular signatures in an automated, unbiased and spatially aware manner. We show the general applicability of multimodal FTIR-guided MALDI-MSI by demonstrating precise tumor localization in mouse brain bearing glioma xenografts and in human primary gastrointestinal stromal tumors. Finally, the presented multimodal tissue analysis method allows for morphology-sensitive lipid signature retrieval from brains of mice suffering from lipidosis caused by Niemann-Pick type C disease. Nature Publishing Group UK 2018-01-10 /pmc/articles/PMC5762902/ /pubmed/29321555 http://dx.doi.org/10.1038/s41598-017-18477-6 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Rabe, Jan-Hinrich A. Sammour, Denis Schulz, Sandra Munteanu, Bogdan Ott, Martina Ochs, Katharina Hohenberger, Peter Marx, Alexander Platten, Michael Opitz, Christiane A. Ory, Daniel S. Hopf, Carsten Fourier Transform Infrared Microscopy Enables Guidance of Automated Mass Spectrometry Imaging to Predefined Tissue Morphologies |
title | Fourier Transform Infrared Microscopy Enables Guidance of Automated Mass Spectrometry Imaging to Predefined Tissue Morphologies |
title_full | Fourier Transform Infrared Microscopy Enables Guidance of Automated Mass Spectrometry Imaging to Predefined Tissue Morphologies |
title_fullStr | Fourier Transform Infrared Microscopy Enables Guidance of Automated Mass Spectrometry Imaging to Predefined Tissue Morphologies |
title_full_unstemmed | Fourier Transform Infrared Microscopy Enables Guidance of Automated Mass Spectrometry Imaging to Predefined Tissue Morphologies |
title_short | Fourier Transform Infrared Microscopy Enables Guidance of Automated Mass Spectrometry Imaging to Predefined Tissue Morphologies |
title_sort | fourier transform infrared microscopy enables guidance of automated mass spectrometry imaging to predefined tissue morphologies |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5762902/ https://www.ncbi.nlm.nih.gov/pubmed/29321555 http://dx.doi.org/10.1038/s41598-017-18477-6 |
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