Neutron-encoded Signatures Enable Product Ion Annotation From Tandem Mass Spectra
peer-reviewed · Molecular & Cellular Proteomics · 2013
| Date | 2013-12-01 |
| Type | peer-reviewed |
| Venue | Molecular & Cellular Proteomics |
| Publisher | Elsevier BV |
| Contribution | adjacent |
| DOI | 10.1074/mcp.m113.028951 |
| Citations (OpenAlex) | 21 |
| Venue 2-year citedness | 4.69 |
Abstract
We report the use of neutron-encoded (NeuCode) stable isotope labeling of amino acids in cell culture for the purpose of C-terminal product ion annotation. Two NeuCode labeling isotopologues of lysine, (13)C6(15)N2 and (2)H8, which differ by 36 mDa, were metabolically embedded in a sample proteome, and the resultant labeled proteins were combined, digested, and analyzed via liquid chromatography and mass spectrometry. With MS/MS scan resolving powers of ~50,000 or higher, product ions containing the C terminus (i.e. lysine) appear as a doublet spaced by exactly 36 mDa, whereas N-terminal fragments exist as a single m/z peak. Through theory and experiment, we demonstrate that over 90% of all y-type product ions have detectable doublets. We report on an algorithm that can extract these neutron signatures with high sensitivity and specificity. In other words, of 15,503 y-type product ion peaks, the y-type ion identification algorithm correctly identified 14,552 (93.2%) based on detection of the NeuCode doublet; 6.8% were misclassified (i.e. other ion types that were assigned as y-type products). Searching NeuCode labeled yeast with PepNovo(+) resulted in a 34% increase in correct de novo identifications relative to searching through MS/MS only. We use this tool to simplify spectra prior to database searching, to sort unmatched tandem mass spectra for spectral richness, for correlation of co-fragmented ions to their parent precursor, and for de novo sequence identification.
Methods and tools
- NeuCode y-ion annotation: Two lysine isotopologues differing by 36 mDa are embedded metabolically, so every C-terminal fragment appears as a resolvable doublet and N-terminal ones do not. An algorithm reads that signature to label y-type ions at 93.2% accuracy, which among other uses lifts correct de novo identifications with PepNovo+ by 34%.
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Cited by (3)
- Classification of B and Y Ions in Peptide MS/MS Spectra Based on Machine Learning (2023) crossref
- UVnovo: A de Novo Sequencing Algorithm Using Single Series of Fragment Ions via Chromophore Tagging and 351 nm Ultraviolet Photodissociation Mass Spectrometry (2016) both
- Application of de Novo Sequencing to Large-Scale Complex Proteomics Data Sets (2016) crossref