Paulovich AG, et al. (2010) Interlaboratory Study Characterizing a Yeast Performance Standard for Benchmarking LC-MS Platform Performance. Mol Cell Proteomics 9(2):242-54
Abstract: Optimal performance of LC-MS/MS platforms is critical to generating high quality proteomic data. Although individual laboratories have developed quality control samples, there is no widely available performance standard of biological complexity (and associated reference datasets) for benchmarking of platform performance for analysis of complex biological proteomes across different laboratories in the community. Individual preparations of the yeast Saccharomyces cerevisiae proteome have been used extensively by laboratories in the proteomic community to characterize LC-MS platform performance. The yeast proteome is uniquely attractive as a performance standard since it is the most extensively characterized complex biological proteome, and the only one associated with several large-scale studies estimating the abundance of all detectable proteins. In this study, we describe a standard operating protocol for large-scale production of the yeast performance standard, and offer aliquots to the community through the National Institute of Standards and Technology, where the yeast proteome is under development as a certified reference material to meet the long-term needs of the community. Using a series of metrics that characterize LC-MS performance, we provide a reference dataset demonstrating typical performance of commonly used ion trap instrument platforms in expert laboratories; the results provide a basis for laboratories to benchmark their own performance, to improve upon current methods, and to evaluate new technologies. Additionally, we demonstrate how the yeast reference, spiked with human proteins, can be used to benchmark the power of proteomic platforms for detection of differentially expressed proteins at different levels of concentration in a complex matrix, thereby providing a metric to evaluate and minimize pre-analytical and analytical variation in comparative proteomics experiments.
|Status: Published||Type: Journal Article||PubMed ID: 19858499|
Topics addressed in this paper
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|Topics||Topics not linked to Genes|
|Large-scale protein detection|
|Other large-scale proteomic analysis|