Quantifying the Impact of Chimera MS/MS Spectra on Peptide Identification in Large-Scale Proteomics Studies

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Abstract
A complicating factor for protein identification within complex mixtures by LC/MS/MS is the problem of “chimera” spectra, where two or more precursor ions with similar mass and retention time are co-sequenced by MS/MS. Chimera spectra show reduced scores due to unidentifiable fragment ions derived from contaminating parents. However, the extent of chimeras in LC/MS/MS data sets and their impact on protein identification workflows are incompletely understood. We report ChimeraCounter, a software program which detects chimeras in data sets collected on an Orbitrap/LTQ instrument. Evaluation of synthetic chimeras created from pairs of well-defined peptide MS/MS spectra reveal that chimeras reduce database search scores most significantly when contaminating fragment ion intensities exceed 20% of the targeted fragment ion intensities. In large-scale data sets, the identification rate for chimera MS/MS is 2-fold lower compared to nonchimera spectra. Importantly, this occurs in a manner which depends not on absolute precursor ion intensity, but on intensity relative to the median precursor intensity distribution. We further show that chimeras reduce the number of accepted peptide identifications by increasing false negatives while showing little increase in false positives. The results provide a framework for identifying chimeras and characterizing their contribution to the poorly understood false negative class of MS/MS.