Computational tools for peptide quantification using mass spectrometry and their application to the proteome of Prochlorococcus marinus MED4.

摘要

We have developed experimental and computational tools for label-free peptide quantification using liquid chromatography coupled to mass spectrometry (LC/MS), applying these methods to the proteome of the cyanobacterium Prochlorococcus marinus MED4 under phosphate starvation.; In Chapter 2, we describe an open-source software package, MapQuant, which permits the comprehensive, rigorous quantification of peptides present in a proteomic sample. MapQuant treats an LC/MS experiment as a 2-D image, one axis representing retention time (rt) and the other m/z units. It thereby permits the use of standard image processing techniques to perform noise filtering, watershed segmentation, peak finding, peak fitting, peak clustering, charge-state determination, and carbon-content estimation. MapQuant reports abundances that respond linearly with the amount of sample analyzed on both low- and high-resolution instruments, over a thousand-fold dynamic range. Added background noise, either as a medium-complexity peptide mixture or as a high-complexity trypsinized proteome, exerts negligible effects on these abundances.; In Chapter 3, we introduce a new XML file format for the representation and storage of raw LCIMS data, rawXML. Three novel concepts are featured in this new data format which improve storage space and random access time: an m/z ruler, zero compression, and a data-separate scan header at the beginning of the file. We show that rawXML file sizes can be as much as three times smaller than the corresponding file sizes generated using the current community standard mzXML.; In Chapter 4, we employ MapQuant in the first label-free quantitative proteomics experiment conducted in parallel with whole-genome mRNA expression analysis, for the study of the cyanobacterium Prochlorococcus marinus MED4 under a time course of phosphate starvation conditions. We introduce quality metrics for the analysis of highthroughput LC/MS data, and show that such data are suited for reliable label-free quantitative proteomics. Second, we describe a straightforward accurate mass/time tag approach for augmenting peptide sequence identification coverage of MapQuant isotopic clusters. We observe ∼60% of the theoretical proteome (> 900 proteins) over the entire time course. At the 48 h time point, 52 proteins are significantly differentially expressed, 8 of which were also observed to be up-regulated at the mRNA level with a comparable fold-increase. These 8 proteins include most of the proteins involved in the phosphate transport and signaling pathways. We discuss these findings with respect to phosphate storage mechanisms and possible proteolytic regulation in MED4 in response to phosphate starvation.