MassIVE MSV000086791

Complete Public PXD023925

MudPIT PTMs analyses of whole cell protein extracts from Saccharomyces cerevisiae grown at 21C and 35C

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Description

Sample preparation, protein digestion, and MS data acquisition are described in MSV000086790. Post-translational Modification Searches | Peak files were extracted using RawDistiller and searched using ProLuCID (v. 1.3.3) against a database consisting of 5,846 S. cerevisiae non-redundant proteins (downloaded from NCBI 11-01-2016), 193 usual contaminants (such as human keratins, IgGs, and proteolytic enzymes), and, to estimate false discovery rates (FDRs), 6039 randomized amino acid sequences derived from each non-redundant protein entry. All cysteines were considered as fully carboxamidomethylated (+57.0215 Da statically added). The MS/MS dataset for the samples only digested with trypsin was further searched for modified peptides in a recursive manner. A total of eight differential modification searches were set up to query for oxidized methionines (+15.9949 Da) in combination with: 1) acetylated lysines, serines, and threonines (+42.0106 Da); 2) formylated arginines and lysines (+27.9949 Da); 3) hydroxylated aspartates, tyrosines, histidines, and prolines (+15.9949); 4) mono- (+14.0157 Da) and 5) dimethylated (+28.0314 Da) arginines and lysines; 6) trimethylated (+42.0470) lysines; 7) phosphorylated (+79.9663 Da) serines, threonines, and tyrosines; and 8) ubiquitinated lysines (+114.0429 Da). Mass tolerances of 7 ppm for precursor and 800 ppm for fragment ions were used. MS/MS datasets generated for trypsin-digested peptides were searched with KR peptide-end requirements. After this round of searches, an in-house software, sqt-merge (Zybailov et al 2005), was used to combine the ProLuCID output files (.sqt files) allowing only the best matches out of the eight differential queries to be ranked first based on cross-correlation scores (XCorr) and for normalized differences between XCorrs (DeltaCn) to be recalculated accordingly. DTASelect v1.9 and swallow v. 0.0.1 (https://github.com/tzw-wen/kite) were used to filter ProLuCID search results at given FDRs at the spectrum, peptide, and protein levels. Here, all controlled FDRs were less than 1%. [doi:10.25345/C5RF7G] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: temperature challenge ; post-translational modifications

Contact

Principal Investigators:
(in alphabetical order) 		Laurence Florens, The Stowers Institute for Medical Research, USA
Submitting User: laflorens

Publications

Domnauer M, Zheng F, Li L, Zhang Y, Chang CE, Unruh JR, Conkright-Fincham J, McCroskey S, Florens L, Zhang Y, Seidel C, Fong B, Schilling B, Sharma R, Ramanathan A, Si K, Zhou C.
Proteome plasticity in response to persistent environmental change.
Mol Cell. 2021 Aug 19;81(16):3294-3309.e12. doi: 10.1016/j.molcel.2021.06.028. Epub 2021 Jul 21. PMID: 34293321.

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