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Metabolite mapping by consecutive nanostructure and silver‐assisted mass spectrometry imaging on tissue sections
Rationale Nanostructure‐based mass spectrometry imaging (MSI) is a promising technology for molecular imaging of small molecules, without the complex chemical background typically encountered in matrix‐assisted molecular imaging approaches. Here, we have enhanced these surfaces with silver (Ag) to p...
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Published in: | Rapid communications in mass spectrometry 2017-06, Vol.31 (12), p.991-1000 |
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creator | Gustafsson, O. J. R. Guinan, T. M. Rudd, D. Kobus, H. Benkendorff, K. Voelcker, N. H. |
description | Rationale
Nanostructure‐based mass spectrometry imaging (MSI) is a promising technology for molecular imaging of small molecules, without the complex chemical background typically encountered in matrix‐assisted molecular imaging approaches. Here, we have enhanced these surfaces with silver (Ag) to provide a second tier of MSI data from a single sample.
Methods
MSI data was acquired through the application of laser desorption/ionization mass spectrometry to biological samples imprinted onto desorption/ionization on silicon (DIOS) substrates. Following initial analysis, ultra‐thin Ag layers were overlaid onto the followed by MSI analysis (Ag‐DIOS MSI). This approach was first demonstrated for fingermark small molecules including environmental contaminants and sebum components. Subsequently, this bimodal method was translated to lipids and metabolites in fore‐stomach sections from a 6‐bromoisatin chemopreventative murine mouse model.
Results
DIOS MSI allowed mapping of common ions in fingermarks as well as 6‐bromoisatin metabolites and lipids in murine fore‐stomach. Furthermore, DIOS MSI was complemented by the Ag‐DIOS MSI of Ag‐adductable lipids such as wax esters in fingermarks and cholesterol in murine fore‐stomach. Gastrointestinal acid condensation products of 6‐bromoisatin, such as the 6,6'‐dibromoindirubin mapped herein, are very challenging to isolate and characterize. By re‐analyzing the same tissue imprints, this metabolite was readily detected by DIOS, placed in a tissue‐specific spatial context, and subsequently overlaid with additional lipid distributions acquired using Ag‐DIOS MSI.
Conclusions
The ability to place metabolite and lipid classes in a tissue‐specific context makes this novel method suited to MSI analyses where the collection of additional information from the same sample maximises resource use, and also maximises the number of annotated small molecules, in particular for metabolites that are typically undetectable with traditional platforms. Copyright © 2017 John Wiley & Sons, Ltd. |
doi_str_mv | 10.1002/rcm.7869 |
format | article |
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Nanostructure‐based mass spectrometry imaging (MSI) is a promising technology for molecular imaging of small molecules, without the complex chemical background typically encountered in matrix‐assisted molecular imaging approaches. Here, we have enhanced these surfaces with silver (Ag) to provide a second tier of MSI data from a single sample.
Methods
MSI data was acquired through the application of laser desorption/ionization mass spectrometry to biological samples imprinted onto desorption/ionization on silicon (DIOS) substrates. Following initial analysis, ultra‐thin Ag layers were overlaid onto the followed by MSI analysis (Ag‐DIOS MSI). This approach was first demonstrated for fingermark small molecules including environmental contaminants and sebum components. Subsequently, this bimodal method was translated to lipids and metabolites in fore‐stomach sections from a 6‐bromoisatin chemopreventative murine mouse model.
Results
DIOS MSI allowed mapping of common ions in fingermarks as well as 6‐bromoisatin metabolites and lipids in murine fore‐stomach. Furthermore, DIOS MSI was complemented by the Ag‐DIOS MSI of Ag‐adductable lipids such as wax esters in fingermarks and cholesterol in murine fore‐stomach. Gastrointestinal acid condensation products of 6‐bromoisatin, such as the 6,6'‐dibromoindirubin mapped herein, are very challenging to isolate and characterize. By re‐analyzing the same tissue imprints, this metabolite was readily detected by DIOS, placed in a tissue‐specific spatial context, and subsequently overlaid with additional lipid distributions acquired using Ag‐DIOS MSI.
Conclusions
The ability to place metabolite and lipid classes in a tissue‐specific context makes this novel method suited to MSI analyses where the collection of additional information from the same sample maximises resource use, and also maximises the number of annotated small molecules, in particular for metabolites that are typically undetectable with traditional platforms. Copyright © 2017 John Wiley & Sons, Ltd.</description><identifier>ISSN: 0951-4198</identifier><identifier>EISSN: 1097-0231</identifier><identifier>DOI: 10.1002/rcm.7869</identifier><identifier>PMID: 28370605</identifier><language>eng</language><publisher>England: Wiley Subscription Services, Inc</publisher><subject>Animals ; Biological properties ; Cholesterol ; Colorectal Neoplasms - chemistry ; Condensates ; Contaminants ; Context ; Data acquisition ; Desorption ; Esters ; Fingerprints ; Imaging ; Ionization ; Laser applications ; Lipids ; Lipids - analysis ; Mapping ; Mass spectrometry ; Mass Spectrometry - methods ; Metabolites ; Metabolome ; Mice ; Mice, Inbred C57BL ; Molecular Imaging - methods ; Nanostructure ; Nanostructures - chemistry ; Silicon substrates ; Silver ; Silver - chemistry ; Spectroscopy ; Stomach ; Stomach - chemistry ; Thin films</subject><ispartof>Rapid communications in mass spectrometry, 2017-06, Vol.31 (12), p.991-1000</ispartof><rights>Copyright © 2017 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3839-12da85eec0493a3cf63fbf66489777bd9e779e4698b1d4fe909b952ae817dad83</citedby><cites>FETCH-LOGICAL-c3839-12da85eec0493a3cf63fbf66489777bd9e779e4698b1d4fe909b952ae817dad83</cites><orcidid>0000-0002-2977-5032 ; 0000-0002-1536-7804</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28370605$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gustafsson, O. J. R.</creatorcontrib><creatorcontrib>Guinan, T. M.</creatorcontrib><creatorcontrib>Rudd, D.</creatorcontrib><creatorcontrib>Kobus, H.</creatorcontrib><creatorcontrib>Benkendorff, K.</creatorcontrib><creatorcontrib>Voelcker, N. H.</creatorcontrib><title>Metabolite mapping by consecutive nanostructure and silver‐assisted mass spectrometry imaging on tissue sections</title><title>Rapid communications in mass spectrometry</title><addtitle>Rapid Commun Mass Spectrom</addtitle><description>Rationale
Nanostructure‐based mass spectrometry imaging (MSI) is a promising technology for molecular imaging of small molecules, without the complex chemical background typically encountered in matrix‐assisted molecular imaging approaches. Here, we have enhanced these surfaces with silver (Ag) to provide a second tier of MSI data from a single sample.
Methods
MSI data was acquired through the application of laser desorption/ionization mass spectrometry to biological samples imprinted onto desorption/ionization on silicon (DIOS) substrates. Following initial analysis, ultra‐thin Ag layers were overlaid onto the followed by MSI analysis (Ag‐DIOS MSI). This approach was first demonstrated for fingermark small molecules including environmental contaminants and sebum components. Subsequently, this bimodal method was translated to lipids and metabolites in fore‐stomach sections from a 6‐bromoisatin chemopreventative murine mouse model.
Results
DIOS MSI allowed mapping of common ions in fingermarks as well as 6‐bromoisatin metabolites and lipids in murine fore‐stomach. Furthermore, DIOS MSI was complemented by the Ag‐DIOS MSI of Ag‐adductable lipids such as wax esters in fingermarks and cholesterol in murine fore‐stomach. Gastrointestinal acid condensation products of 6‐bromoisatin, such as the 6,6'‐dibromoindirubin mapped herein, are very challenging to isolate and characterize. By re‐analyzing the same tissue imprints, this metabolite was readily detected by DIOS, placed in a tissue‐specific spatial context, and subsequently overlaid with additional lipid distributions acquired using Ag‐DIOS MSI.
Conclusions
The ability to place metabolite and lipid classes in a tissue‐specific context makes this novel method suited to MSI analyses where the collection of additional information from the same sample maximises resource use, and also maximises the number of annotated small molecules, in particular for metabolites that are typically undetectable with traditional platforms. Copyright © 2017 John Wiley & Sons, Ltd.</description><subject>Animals</subject><subject>Biological properties</subject><subject>Cholesterol</subject><subject>Colorectal Neoplasms - chemistry</subject><subject>Condensates</subject><subject>Contaminants</subject><subject>Context</subject><subject>Data acquisition</subject><subject>Desorption</subject><subject>Esters</subject><subject>Fingerprints</subject><subject>Imaging</subject><subject>Ionization</subject><subject>Laser applications</subject><subject>Lipids</subject><subject>Lipids - analysis</subject><subject>Mapping</subject><subject>Mass spectrometry</subject><subject>Mass Spectrometry - methods</subject><subject>Metabolites</subject><subject>Metabolome</subject><subject>Mice</subject><subject>Mice, Inbred C57BL</subject><subject>Molecular Imaging - methods</subject><subject>Nanostructure</subject><subject>Nanostructures - chemistry</subject><subject>Silicon substrates</subject><subject>Silver</subject><subject>Silver - chemistry</subject><subject>Spectroscopy</subject><subject>Stomach</subject><subject>Stomach - chemistry</subject><subject>Thin films</subject><issn>0951-4198</issn><issn>1097-0231</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp1kdGK1TAQhoMo7nEVfAIJeONN10zTNsmlHHRX2EUQvQ5pOl2ytE3NpCvnzkfwGX0Sc9xVQfBqbr75-Gd-xp6DOAMh6tfJz2dKd-YB24EwqhK1hIdsJ0wLVQNGn7AnRDdCALS1eMxOai2V6ES7Y-kKs-vjFDLy2a1rWK55f-A-LoR-y-EW-eKWSDltPm8JuVsGTmG6xfTj23dHFCjjUFaJOK3oc4oz5nTgYXbXR1lceA5EG_IizKF4n7JHo5sIn93PU_b53dtP-4vq8sP5-_2by8pLLU0F9eB0i-hFY6STfuzk2I9d12ijlOoHg0oZbDqjexiaEY0wvWlrhxrU4AYtT9mrO--a4pcNKds5kMdpcgvGjSxo3YASsoWCvvwHvYlbWko6C0ZAo4yum79CnyJRwtGuqZyZDhaEPfZgSw_22ENBX9wLt37G4Q_4-_EFqO6Ar2HCw39F9uP-6pfwJ8WTlM0</recordid><startdate>20170630</startdate><enddate>20170630</enddate><creator>Gustafsson, O. J. R.</creator><creator>Guinan, T. M.</creator><creator>Rudd, D.</creator><creator>Kobus, H.</creator><creator>Benkendorff, K.</creator><creator>Voelcker, N. H.</creator><general>Wiley Subscription Services, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-2977-5032</orcidid><orcidid>https://orcid.org/0000-0002-1536-7804</orcidid></search><sort><creationdate>20170630</creationdate><title>Metabolite mapping by consecutive nanostructure and silver‐assisted mass spectrometry imaging on tissue sections</title><author>Gustafsson, O. J. R. ; Guinan, T. M. ; Rudd, D. ; Kobus, H. ; Benkendorff, K. ; Voelcker, N. H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3839-12da85eec0493a3cf63fbf66489777bd9e779e4698b1d4fe909b952ae817dad83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Animals</topic><topic>Biological properties</topic><topic>Cholesterol</topic><topic>Colorectal Neoplasms - chemistry</topic><topic>Condensates</topic><topic>Contaminants</topic><topic>Context</topic><topic>Data acquisition</topic><topic>Desorption</topic><topic>Esters</topic><topic>Fingerprints</topic><topic>Imaging</topic><topic>Ionization</topic><topic>Laser applications</topic><topic>Lipids</topic><topic>Lipids - analysis</topic><topic>Mapping</topic><topic>Mass spectrometry</topic><topic>Mass Spectrometry - methods</topic><topic>Metabolites</topic><topic>Metabolome</topic><topic>Mice</topic><topic>Mice, Inbred C57BL</topic><topic>Molecular Imaging - methods</topic><topic>Nanostructure</topic><topic>Nanostructures - chemistry</topic><topic>Silicon substrates</topic><topic>Silver</topic><topic>Silver - chemistry</topic><topic>Spectroscopy</topic><topic>Stomach</topic><topic>Stomach - chemistry</topic><topic>Thin films</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gustafsson, O. J. R.</creatorcontrib><creatorcontrib>Guinan, T. M.</creatorcontrib><creatorcontrib>Rudd, D.</creatorcontrib><creatorcontrib>Kobus, H.</creatorcontrib><creatorcontrib>Benkendorff, K.</creatorcontrib><creatorcontrib>Voelcker, N. H.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Engineered Materials Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>MEDLINE - Academic</collection><jtitle>Rapid communications in mass spectrometry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gustafsson, O. J. R.</au><au>Guinan, T. M.</au><au>Rudd, D.</au><au>Kobus, H.</au><au>Benkendorff, K.</au><au>Voelcker, N. H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Metabolite mapping by consecutive nanostructure and silver‐assisted mass spectrometry imaging on tissue sections</atitle><jtitle>Rapid communications in mass spectrometry</jtitle><addtitle>Rapid Commun Mass Spectrom</addtitle><date>2017-06-30</date><risdate>2017</risdate><volume>31</volume><issue>12</issue><spage>991</spage><epage>1000</epage><pages>991-1000</pages><issn>0951-4198</issn><eissn>1097-0231</eissn><abstract>Rationale
Nanostructure‐based mass spectrometry imaging (MSI) is a promising technology for molecular imaging of small molecules, without the complex chemical background typically encountered in matrix‐assisted molecular imaging approaches. Here, we have enhanced these surfaces with silver (Ag) to provide a second tier of MSI data from a single sample.
Methods
MSI data was acquired through the application of laser desorption/ionization mass spectrometry to biological samples imprinted onto desorption/ionization on silicon (DIOS) substrates. Following initial analysis, ultra‐thin Ag layers were overlaid onto the followed by MSI analysis (Ag‐DIOS MSI). This approach was first demonstrated for fingermark small molecules including environmental contaminants and sebum components. Subsequently, this bimodal method was translated to lipids and metabolites in fore‐stomach sections from a 6‐bromoisatin chemopreventative murine mouse model.
Results
DIOS MSI allowed mapping of common ions in fingermarks as well as 6‐bromoisatin metabolites and lipids in murine fore‐stomach. Furthermore, DIOS MSI was complemented by the Ag‐DIOS MSI of Ag‐adductable lipids such as wax esters in fingermarks and cholesterol in murine fore‐stomach. Gastrointestinal acid condensation products of 6‐bromoisatin, such as the 6,6'‐dibromoindirubin mapped herein, are very challenging to isolate and characterize. By re‐analyzing the same tissue imprints, this metabolite was readily detected by DIOS, placed in a tissue‐specific spatial context, and subsequently overlaid with additional lipid distributions acquired using Ag‐DIOS MSI.
Conclusions
The ability to place metabolite and lipid classes in a tissue‐specific context makes this novel method suited to MSI analyses where the collection of additional information from the same sample maximises resource use, and also maximises the number of annotated small molecules, in particular for metabolites that are typically undetectable with traditional platforms. Copyright © 2017 John Wiley & Sons, Ltd.</abstract><cop>England</cop><pub>Wiley Subscription Services, Inc</pub><pmid>28370605</pmid><doi>10.1002/rcm.7869</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-2977-5032</orcidid><orcidid>https://orcid.org/0000-0002-1536-7804</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Animals Biological properties Cholesterol Colorectal Neoplasms - chemistry Condensates Contaminants Context Data acquisition Desorption Esters Fingerprints Imaging Ionization Laser applications Lipids Lipids - analysis Mapping Mass spectrometry Mass Spectrometry - methods Metabolites Metabolome Mice Mice, Inbred C57BL Molecular Imaging - methods Nanostructure Nanostructures - chemistry Silicon substrates Silver Silver - chemistry Spectroscopy Stomach Stomach - chemistry Thin films |
title | Metabolite mapping by consecutive nanostructure and silver‐assisted mass spectrometry imaging on tissue sections |
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