dc.creatorCharris Molina, Andres Fernando
dc.creatorRiquelme, Gabriel
dc.creatorBurdisso, Paula
dc.creatorHoijemberg, Pablo Ariel
dc.date.accessioned2021-04-14T12:02:55Z
dc.date.accessioned2022-10-15T00:05:04Z
dc.date.available2021-04-14T12:02:55Z
dc.date.available2022-10-15T00:05:04Z
dc.date.created2021-04-14T12:02:55Z
dc.date.issued2019-05
dc.identifierCharris Molina, Andres Fernando; Riquelme, Gabriel; Burdisso, Paula; Hoijemberg, Pablo Ariel; Tackling the Peak Overlap Issue in NMR Metabolomics Studies: 1D Projected Correlation Traces from Statistical Correlation Analysis on Nontilted 2D 1 H NMR J-Resolved Spectra; American Chemical Society; Journal of Proteome Research; 18; 5; 5-2019; 2241-2253
dc.identifier1535-3893
dc.identifierhttp://hdl.handle.net/11336/130002
dc.identifierCONICET Digital
dc.identifierCONICET
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4322713
dc.description.abstractThe identification of metabolites in complex biological matrices is a challenging task in 1D 1 H-NMR-based metabolomics studies. Statistical total correlation spectroscopy (STOCSY) has emerged for aiding the structural elucidation by revealing the peaks that present a high correlation to a driver peak of interest (which would likely belong to the same molecule). However, in these studies, the signals from metabolites are normally present as a mixture of overlapping resonances, limiting the performance of STOCSY. As an alternative to avoid the overlap issue, 2D 1 H homonuclear J-resolved (JRES) spectra were projected, in their usual tilted and symmetrized processed form, and STOCSY was applied on these 1D projections (p-JRES-STOCSY). Nonetheless, this approach suffers in cases where the signals are very close. In addition, STOCSY was applied to the whole JRES spectra (also tilted) to identify correlated multiplets, although the overlap issue in itself was not addressed directly and the subsequent search in databases is complicated in cases of higher order coupling. With these limitations in mind, in the present work, we propose a new methodology based on the application of STOCSY on a set of nontilted JRES spectra, detecting peaks that would overlap in 1D spectra of the same sample set. Correlation comparison analysis for peak overlap detection (COCOA-POD) is able to reconstruct projected 1D STOCSY traces that result in more suitable database queries, as all peaks are summed at their f2 resonances instead of the resonance corresponding to the multiplet center in the tilted JRES spectra. (The peak dispersion and resolution enhancement gained are not sacrificed by the projection.) Besides improving database queries with better peak lists obtained from the projections of the 2D STOCSY analysis, the overlap region is examined, and the multiplet itself is analyzed from the correlation trace at 45° to obtain a cleaner multiplet profile, free from contributions from uncorrelated neighboring peaks.
dc.languageeng
dc.publisherAmerican Chemical Society
dc.relationinfo:eu-repo/semantics/altIdentifier/url/https://pubs.acs.org/doi/pdf/10.1021/acs.jproteome.9b00093
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1021/acs.jproteome.9b00093
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectCOMPLEX MIXTURE
dc.subjectCORRELATION MATRIX
dc.subjectDATABASE
dc.subjectIDENTIFICATION
dc.subjectJ-RESOLVED
dc.subjectMETABOLITE
dc.subjectMETABOLOMICS
dc.subjectNMR
dc.subjectOVERLAP
dc.subjectSTOCSY
dc.titleTackling the Peak Overlap Issue in NMR Metabolomics Studies: 1D Projected Correlation Traces from Statistical Correlation Analysis on Nontilted 2D 1 H NMR J-Resolved Spectra
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:ar-repo/semantics/artículo
dc.typeinfo:eu-repo/semantics/publishedVersion


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