dc.contributor.author | Bhat, Vadiraja B. | |
dc.contributor.author | Seneviratne, Uthpala Indrajith | |
dc.contributor.author | Nott, Alexander | |
dc.contributor.author | Kodihalli, Ravindra | |
dc.contributor.author | Wishnok, John S | |
dc.contributor.author | Tsai, Li-Huei | |
dc.contributor.author | Tannenbaum, Steven R | |
dc.date.accessioned | 2017-05-24T20:03:16Z | |
dc.date.available | 2017-05-24T20:03:16Z | |
dc.date.issued | 2016-04 | |
dc.date.submitted | 2015-10 | |
dc.identifier.issn | 0027-8424 | |
dc.identifier.issn | 1091-6490 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/109331 | |
dc.description.abstract | Protein S-nitrosation (SNO-protein), the nitric oxide-mediated posttranslational modification of cysteine thiols, is an important regulatory mechanism of protein function in both physiological and pathological pathways. A key first step toward elucidating the mechanism by which S-nitrosation modulates a protein’s function is identification of the targeted cysteine residues. Here, we present a strategy for the simultaneous identification of SNO-cysteine sites and their cognate proteins to profile the brain of the CK-p25–inducible mouse model of Alzheimer’s disease-like neurodegeneration. The approach—SNOTRAP (SNO trapping by triaryl phosphine)—is a direct tagging strategy that uses phosphine-based chemical probes, allowing enrichment of SNO-peptides and their identification by liquid chromatography tandem mass spectrometry. SNOTRAP identified 313 endogenous SNO-sites in 251 proteins in the mouse brain, of which 135 SNO-proteins were detected only during neurodegeneration. S-nitrosation in the brain shows regional differences and becomes elevated during early stages of neurodegeneration in the CK-p25 mouse. The SNO-proteome during early neurodegeneration identified increased S-nitrosation of proteins important for synapse function, metabolism, and Alzheimer’s disease pathology. In the latter case, proteins related to amyloid precursor protein processing and secretion are S-nitrosated, correlating with increased amyloid formation. Sequence analysis of SNO-cysteine sites identified potential linear motifs that are altered under pathological conditions. Collectively, SNOTRAP is a direct tagging tool for global elucidation of the SNO-proteome, providing functional insights of endogenous SNO proteins in the brain and its dysregulation during neurodegeneration. | en_US |
dc.description.sponsorship | National Institutes of Health (U.S.) (NIH Grant CA26731) | en_US |
dc.description.sponsorship | Massachusetts Institute of Technology. Center for Environmental Health Sciences (Grant ES002109) | en_US |
dc.description.sponsorship | Simons Foundation | en_US |
dc.description.sponsorship | National Institutes of Health (U.S.) (NIH Grant R01 NS051874) | en_US |
dc.language.iso | en_US | |
dc.publisher | National Academy of Sciences (U.S.) | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1073/pnas.1521318113 | 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 | PNAS | en_US |
dc.title | S-nitrosation of proteins relevant to Alzheimer’s disease during early stages of neurodegeneration | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Seneviratne, Uthpala, Alexi Nott, Vadiraja B. Bhat, Kodihalli C. Ravindra, John S. Wishnok, Li-Huei Tsai, and Steven R. Tannenbaum. “ S-Nitrosation of Proteins Relevant to Alzheimer’s Disease During Early Stages of Neurodegeneration .” Proceedings of the National Academy of Sciences 113, no. 15 (March 24, 2016): 4152–4157. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Biological Engineering | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Chemistry | en_US |
dc.contributor.department | Picower Institute for Learning and Memory | en_US |
dc.contributor.mitauthor | Seneviratne, Uthpala Indrajith | |
dc.contributor.mitauthor | Nott, Alexander | |
dc.contributor.mitauthor | Kodihalli, Ravindra | |
dc.contributor.mitauthor | Wishnok, John S | |
dc.contributor.mitauthor | Tsai, Li-Huei | |
dc.contributor.mitauthor | Tannenbaum, Steven R | |
dc.relation.journal | Proceedings of the National Academy of Sciences of the United States of America | en_US |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dspace.orderedauthors | Seneviratne, Uthpala; Nott, Alexi; Bhat, Vadiraja B.; Ravindra, Kodihalli C.; Wishnok, John S.; Tsai, Li-Huei; Tannenbaum, Steven R. | en_US |
dspace.embargo.terms | N | en_US |
dc.identifier.orcid | https://orcid.org/0000-0001-6774-9639 | |
dc.identifier.orcid | https://orcid.org/0000-0002-2029-7193 | |
dc.identifier.orcid | https://orcid.org/0000-0002-2325-552X | |
dc.identifier.orcid | https://orcid.org/0000-0003-1262-0592 | |
mit.license | PUBLISHER_POLICY | en_US |
mit.metadata.status | Complete | |