Maintenance of Deep Lung Architecture and Automated Airway Segmentation for 3D Mass Spectrometry Imaging

Abstract Mass spectrometry imaging (MSI) is a technique for mapping the spatial distributions of molecules in sectioned tissue. Histology-preserving tissue preparation methods are central to successful MSI studies. Common fixation methods, used to preserve tissue morphology, can result in artifacts...

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Autores principales:	Alison J. Scott, Courtney E. Chandler, Shane R. Ellis, Ron M. A. Heeren, Robert K. Ernst
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d90f40ba5d1948348e6bbd64189f9323
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spelling	oai:doaj.org-article:d90f40ba5d1948348e6bbd64189f93232021-12-02T13:56:50ZMaintenance of Deep Lung Architecture and Automated Airway Segmentation for 3D Mass Spectrometry Imaging10.1038/s41598-019-56364-42045-2322https://doaj.org/article/d90f40ba5d1948348e6bbd64189f93232019-12-01T00:00:00Zhttps://doi.org/10.1038/s41598-019-56364-4https://doaj.org/toc/2045-2322Abstract Mass spectrometry imaging (MSI) is a technique for mapping the spatial distributions of molecules in sectioned tissue. Histology-preserving tissue preparation methods are central to successful MSI studies. Common fixation methods, used to preserve tissue morphology, can result in artifacts in the resulting MSI experiment including delocalization of analytes, altered adduct profiles, and loss of key analytes due to irreversible cross-linking and diffusion. This is especially troublesome in lung and airway samples, in which histology and morphology is best interpreted from 3D reconstruction, requiring the large and small airways to remain inflated during analysis. Here, we developed an MSI-compatible inflation containing as few exogenous components as possible, forgoing perfusion, fixation, and addition of salt solutions upon inflation that resulted in an ungapped 3D molecular reconstruction through more than 300 microns. We characterized a series of polyunsaturated phospholipids (PUFA-PLs), specifically phosphatidylinositol (-PI) lipids linked to lethal inflammation in bacterial infection and mapped them in serial sections of inflated mouse lung. PUFA-PIs were identified using spatial lipidomics and determined to be determinant markers of major airway features using unsupervised hierarchical clustering. Deep lung architecture was preserved using this inflation approach and the resulting sections are compatible with multiple MSI modalities, automated interpretation software, and serial 3D reconstruction.Alison J. ScottCourtney E. ChandlerShane R. EllisRon M. A. HeerenRobert K. ErnstNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 9, Iss 1, Pp 1-12 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Alison J. Scott Courtney E. Chandler Shane R. Ellis Ron M. A. Heeren Robert K. Ernst Maintenance of Deep Lung Architecture and Automated Airway Segmentation for 3D Mass Spectrometry Imaging
description	Abstract Mass spectrometry imaging (MSI) is a technique for mapping the spatial distributions of molecules in sectioned tissue. Histology-preserving tissue preparation methods are central to successful MSI studies. Common fixation methods, used to preserve tissue morphology, can result in artifacts in the resulting MSI experiment including delocalization of analytes, altered adduct profiles, and loss of key analytes due to irreversible cross-linking and diffusion. This is especially troublesome in lung and airway samples, in which histology and morphology is best interpreted from 3D reconstruction, requiring the large and small airways to remain inflated during analysis. Here, we developed an MSI-compatible inflation containing as few exogenous components as possible, forgoing perfusion, fixation, and addition of salt solutions upon inflation that resulted in an ungapped 3D molecular reconstruction through more than 300 microns. We characterized a series of polyunsaturated phospholipids (PUFA-PLs), specifically phosphatidylinositol (-PI) lipids linked to lethal inflammation in bacterial infection and mapped them in serial sections of inflated mouse lung. PUFA-PIs were identified using spatial lipidomics and determined to be determinant markers of major airway features using unsupervised hierarchical clustering. Deep lung architecture was preserved using this inflation approach and the resulting sections are compatible with multiple MSI modalities, automated interpretation software, and serial 3D reconstruction.
format	article
author	Alison J. Scott Courtney E. Chandler Shane R. Ellis Ron M. A. Heeren Robert K. Ernst
author_facet	Alison J. Scott Courtney E. Chandler Shane R. Ellis Ron M. A. Heeren Robert K. Ernst
author_sort	Alison J. Scott
title	Maintenance of Deep Lung Architecture and Automated Airway Segmentation for 3D Mass Spectrometry Imaging
title_short	Maintenance of Deep Lung Architecture and Automated Airway Segmentation for 3D Mass Spectrometry Imaging
title_full	Maintenance of Deep Lung Architecture and Automated Airway Segmentation for 3D Mass Spectrometry Imaging
title_fullStr	Maintenance of Deep Lung Architecture and Automated Airway Segmentation for 3D Mass Spectrometry Imaging
title_full_unstemmed	Maintenance of Deep Lung Architecture and Automated Airway Segmentation for 3D Mass Spectrometry Imaging
title_sort	maintenance of deep lung architecture and automated airway segmentation for 3d mass spectrometry imaging
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/d90f40ba5d1948348e6bbd64189f9323
work_keys_str_mv	AT alisonjscott maintenanceofdeeplungarchitectureandautomatedairwaysegmentationfor3dmassspectrometryimaging AT courtneyechandler maintenanceofdeeplungarchitectureandautomatedairwaysegmentationfor3dmassspectrometryimaging AT shanerellis maintenanceofdeeplungarchitectureandautomatedairwaysegmentationfor3dmassspectrometryimaging AT ronmaheeren maintenanceofdeeplungarchitectureandautomatedairwaysegmentationfor3dmassspectrometryimaging AT robertkernst maintenanceofdeeplungarchitectureandautomatedairwaysegmentationfor3dmassspectrometryimaging
_version_	1718392350350245888

Maintenance of Deep Lung Architecture and Automated Airway Segmentation for 3D Mass Spectrometry Imaging

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