dc.contributor.author | Wang, Xin | |
dc.contributor.author | Garcia, Carlos T. | |
dc.contributor.author | Gong, Guanyu | |
dc.contributor.author | Wishnok, John S | |
dc.contributor.author | Tannenbaum, Steven R | |
dc.date.accessioned | 2019-02-21T15:06:43Z | |
dc.date.available | 2019-02-21T15:06:43Z | |
dc.date.issued | 2018-02 | |
dc.date.submitted | 2017-10 | |
dc.identifier.issn | 0003-2700 | |
dc.identifier.issn | 1520-6882 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/120517 | |
dc.description.abstract | S-Nitrosothiols (RSNOs) constitute a circulating endogenous reservoir of nitric oxide and have important biological activities. In this study, an online coupling of solid-phase derivatization (SPD) with liquid chromatography-mass spectrometry (LC-MS) was developed and applied in the analysis of low-molecular-mass RSNOs. A derivatizing-reagent-modified polymer monolithic column was prepared and adapted for online SPD-LC-MS. Analytes from the LC autosampler flowed through the monolithic column for derivatization and then directly into the LC-MS for analysis. This integration of the online derivatization, LC separation, and MS detection facilitated system automation, allowing rapid, laborsaving, and sensitive detection of RSNOs. S-Nitrosoglutathione (GSNO) was quantified using this automated online method with good linearity (R[superscript 2] = 0.9994); the limit of detection was 0.015 nM. The online SPD-LC-MS method has been used to determine GSNO levels in mouse samples, 138 ± 13.2 nM of endogenous GSNO was detected in mouse plasma. Besides, the GSNO concentrations in liver (64.8 ± 11.3 pmol/mg protein), kidney (47.2 ± 6.1 pmol/mg protein), heart (8.9 ± 1.8 pmol/mg protein), muscle (1.9 ± 0.3 pmol/mg protein), hippocampus (5.3 ± 0.9 pmol/mg protein), striatum (6.7 ± 0.6 pmol/mg protein), cerebellum (31.4 ± 6.5 pmol/mg protein), and cortex (47.9 ± 4.6 pmol/mg protein) were also successfully quantified. When the derivatization was performed within 8 min, followed by LC-MS detection, samples could be rapidly analyzed compared with the offline manual method. Other low-molecular-mass RSNOs, such as S-nitrosocysteine and S-nitrosocysteinylglycine, were captured by rapid precursor-ion scanning, showing that the proposed method is a potentially powerful tool for capture, identification, and quantification of RSNOs in biological samples. | en_US |
dc.description.sponsorship | National Institutes of Health (U.S.) (Grant CA26731) | en_US |
dc.description.sponsorship | National Institutes of Health (U.S.) (Grant ES-002109) | en_US |
dc.publisher | American Chemical Society (ACS) | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1021/ACS.ANALCHEM.7B04049 | en_US |
dc.rights | Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. | en_US |
dc.source | PMC | en_US |
dc.title | Automated Online Solid-Phase Derivatization for Sensitive Quantification of Endogenous | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Wang, Xin, Carlos T. Garcia, Guanyu Gong, John S. Wishnok, and Steven R. Tannenbaum. “Automated Online Solid-Phase Derivatization for Sensitive Quantification of Endogenous S-Nitrosoglutathione and Rapid Capture of Other Low-Molecular-Mass S-Nitrosothiols.” Analytical Chemistry 90, no. 3 (January 9, 2018): 1967–1975. © 2017 American Chemical Society | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Biological Engineering | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Chemistry | en_US |
dc.contributor.mitauthor | Wang, Xin | |
dc.contributor.mitauthor | Garcia, Carlos T. | |
dc.contributor.mitauthor | Gong, Guanyu | |
dc.contributor.mitauthor | Wishnok, John S | |
dc.contributor.mitauthor | Tannenbaum, Steven R | |
dc.relation.journal | Analytical Chemistry | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2019-02-08T13:26:35Z | |
dspace.orderedauthors | Wang, Xin; Garcia, Carlos T.; Gong, Guanyu; Wishnok, John S.; Tannenbaum, Steven R. | en_US |
dspace.embargo.terms | N | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-2325-552X | |
mit.license | PUBLISHER_POLICY | en_US |