Quantitative and In-Depth Survey of the Isotopic Abundance Distribution Errors in Shotgun Proteomics.

Abstract

Accuracy is an important metric when mass spectrometry (MS) is used in large-scale quantitative proteomics research. For MS-based quantification by extracting ion chromatogram (XIC), both the mass and intensity dimensions must be accurate. Although much research has focused on mass accuracy in recent years, less attention has been paid to intensity errors. Here, we investigated signal intensity measurement errors systematically and quantitatively using the natural properties of isotopic distributions. First, we defined a normalized isotopic abundance error model and presented its merits and demerits. Second, a comprehensive survey of the isotopic abundance errors using data sets with increasing sample complexities and concentrations was performed. We examined parameters such as error distribution, relationships between signal intensities within one isotopic cluster, and correlations between different peak errors in isotopic profiles. Our data demonstrated that the high resolution MS platforms might also generate large isotopic intensity measurement errors (approximately 20%). Meanwhile, this error can be reduced to less than 5% using a novel correction algorithm, which is based on the theoretical isotopic abundance distribution. Finally, a nonlinear relationship was observed as the abundance error decreased in isotopic profiles with higher intensity. Our findings are expected to provide insight into isotopic abundance recalibration in quantitative proteomics.