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dc.creatorVeličković, Dušan
dc.creatorZhang, Guanshi
dc.creatorBezbradica, Dejan
dc.creatorBhattacharjee, Arunima
dc.creatorPasa-Tolić, Ljiljana
dc.creatorSharma, Kumar
dc.creatorAlexandrov, Theodore
dc.creatorAnderton, Christopher R.
dc.date.accessioned2021-03-10T14:22:09Z
dc.date.available2021-03-10T14:22:09Z
dc.date.issued2020
dc.identifier.issn1044-0305
dc.identifier.urihttp://TechnoRep.tmf.bg.ac.rs/handle/123456789/4489
dc.description.abstractAutomated spraying devices have become ubiquitous in laboratories employing matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), in part because they permit control of a number of matrix application parameters that can easily be reproduced for intra- and interlaboratory studies. Determining the optimal parameters for MALDI matrix application, such as temperature, flow rate, spraying velocity, number of spraying cycles, and solvent composition for matrix application, is critical for obtaining high-quality MALDI-MSI data. However, there are no established approaches for optimizing these multiple parameters simultaneously. Instead optimization is performed iteratively (i.e., one parameter at a time), which is time-consuming and can lead to overall nonoptimal settings. In this report, we demonstrate the use a novel experimental design and the response surface methodology to optimize five parameters of MALDI matrix application using a robotic sprayer. Thirty-two combinations of MALDI matrix spraying conditions were tested, which allowed us to elucidate relationships between each of the application parameters as determined by MALDI-MS (specifically, using a 15 T Fourier transform ion cyclotron resonance mass spectrometer). As such, we were able to determine the optimal automated spraying parameters that minimized signal delocalization and enabled high MALDI sensitivity. We envision this optimization strategy can be utilized for other matrix application approaches and MALDI-MSI analyses of other molecular classes and tissue types.en
dc.publisherAmer Chemical Soc, Washington
dc.relationNIH-NIDDKUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Diabetes & Digestive & Kidney Diseases (NIDDK) [1UG3DK114920-01]
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/634402/EU//
dc.relationERC Consolidator grant METACELL
dc.relationOffice of Biological and Environmental Research
dc.relationDOEUnited States Department of Energy (DOE) [DE-AC05-76RLO1830]
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/777222/EU//
dc.rightsopenAccess
dc.sourceJournal of the American Society for Mass Spectrometry
dc.subjectexperimental designen
dc.subjectMETASPACEen
dc.subjectmolecular annotationen
dc.subjectdelocalization quantificationen
dc.subjecthuman biopsyen
dc.titleResponse Surface Methodology As a New Approach for Finding Optimal MALDI Matrix Spraying Parameters for Mass Spectrometry Imagingen
dc.typearticle
dc.rights.licenseARR
dc.citation.epage516
dc.citation.issue3
dc.citation.other31(3): 508-516
dc.citation.rankM21~
dc.citation.spage508
dc.citation.volume31
dc.identifier.doi10.1021/jasms.9b00074
dc.identifier.fulltexthttp://TechnoRep.tmf.bg.ac.rs/bitstream/id/10365/jasms.9b00074.pdf
dc.identifier.pmid32126772
dc.identifier.rcubconv_6067
dc.identifier.scopus2-s2.0-85081041220
dc.identifier.wos000518702500006
dc.type.versionpublishedVersion


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