Benchmarking accuracy and precision of intensity-based absolute quantification of protein abundances in Saccharomyces cerevisiae

Protein quantification via label-free mass spectrometry (MS) has become an increasingly popular method for predicting genome-wide absolute protein abundances. A known caveat of this approach, however, is the poor technical reproducibility, that is, how consistent predictions are when the same sample is measured repeatedly. Here, we measured proteomics data for Saccharomyces cerevisiae with both biological and inter-batch technical triplicates, to analyze both accuracy and precision of protein quantification via MS. Moreover, we analyzed how these metrics vary when applying different methods for converting MS intensities to absolute protein abundances. We demonstrate that our simple normalization and rescaling approach can perform as accurately, yet more precisely, than methods which rely on external standards. Additionally, we show that inter-batch reproducibility is worse than biological reproducibility for all evaluated methods. These results offer a new benchmark for assessing MS data quality for protein quantification, while also underscoring current limitations in this approach.

Automated summary

Protein quantification via label-free mass spectrometry is a popular method for predicting genome-wide absolute protein abundances, but suffers from poor technical reproducibility. This study demonstrates that a simple normalization and rescaling approach can perform as accurately, yet more precisely, than methods relying on external standards. Additionally, it shows that inter-batch reproducibility is worse than biological reproducibility for all evaluated methods, providing a new benchmark for assessing MS data quality for protein quantification.