Abstract
Conventional LC-MS/MS data analysis matches each precursor ion and fragmentation pattern to their best fit within databases of theoretical spectra, yielding a peptide identification. Confidence is estimated by a score but can be validated by statistics, false discovery rates, and/or manual validation. A weakness is that each ion is evaluated independently, discarding potentially useful cross-correlations. In a classical approach to de novo sequence analysis, mixtures of peptides differing only in a carboxyl-terminal isotopic label yield fragmentation spectra with single, unlabeled b-type ions but pairs of isotope-labeled y-type ions, facilitating confident assignments. To apply this principle to identification by fragmentation pattern matching, we developed Validator, software that recognizes isotopic peptide pairs and compares their identifications and fragmentation patterns. Testing Validator 1 on a Mascot results file from FT-ICR LC-MS/MS of (16)O/(18)O-labeled yeast cell lysate peptides yielded 2,775 peptide pairs sharing a common identification but differing in carboxyl-terminal label. Comparing observed b- and y-ions with the predicted fragmentation pattern improved the threshold Mascot score for 5% false discovery from 36 to 22, significantly increasing both sensitivity and specificity. Validator 2, which identifies pairs by precursor mass difference alone before comparing observed fragmentation with that predicted by Mascot, found 2,021 isotopic pairs, similarly achieving improved sensitivity and specificity. Finally Validator 3, which finds pairs based on mass difference alone and then deconvolutes fragmentation patterns independently of Mascot, found 964 predicted peptides. Validator 3 allowed raw mass spectrometry data to be mined not only to validate Mascot results but also to discover peptides missed by Mascot. Using standard desktop hardware, the Validator 1-3 software processed the 11,536 spectra in the 93-MB Mascot .DAT file in less than 6 min (32 spectra/s), revealing high confidence peptide identifications without regard to Mascot score, far faster than manual or other independent validation methods.
Highlights
Conventional LC-MS/MS data analysis matches each precursor ion and fragmentation pattern to their best fit within databases of theoretical spectra, yielding a peptide identification
We have developed Validator, a novel proteomics database search validation software that provides a direct and independent means to validate peptide identifications provided by Mascot analysis of tandem mass spectrometry data
Our algorithm is based on LC-MS/MS analysis of a mixture of carboxyl-terminal stable isotope-labeled and non-labeled peptides, a common sample in quantitative mass spectrometry [32, 53–57]
Summary
Conventional LC-MS/MS data analysis matches each precursor ion and fragmentation pattern to their best fit within databases of theoretical spectra, yielding a peptide identification. In a classical approach to de novo sequence analysis, mixtures of peptides differing only in a carboxylterminal isotopic label yield fragmentation spectra with single, unlabeled b-type ions but pairs of isotope-labeled y-type ions, facilitating confident assignments. To apply this principle to identification by fragmentation pattern matching, we developed Validator, software that recognizes isotopic peptide pairs and compares their identifications and fragmentation patterns. What these algorithms share is the determination of a score for a spectrum-peptide match and subsequently a protein identification, and it is the way in which these scores are assigned and interpreted that distinguishes them [19]
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