Trypsin catalyzed 16O-to-18O exchange for comparative proteomics: tandem mass spectrometry comparison using MALDI-TOF, ESI-QTOF, and ESI-ion trap mass spectrometers.

Quantitative or comparative proteome analysis was initially performed with 2-dimensional gel electrophoresis with the inherent disadvantages of being biased towards certain proteins and being labor intensive. Alternative mass spectrometry-based approaches in conjunction with gel-free protein/peptide separation have been developed in recent years using various stable isotope labeling techniques. Common to all these techniques is the incorporation, biosynthetically or chemically, of a labeling moiety having either a natural isotope distribution of hydrogen, carbon, oxygen, or nitrogen (light form) or being enriched with heavy isotopes like deuterium, (13)C, (18)O, or (15)N, respectively. By mixing equal amounts of a control sample possessing for instance the light form of the label with a heavy-labeled case sample, differentially labeled peptides are detected by mass spectrometric methods and their intensities serve as a means for direct relative protein quantification. While each of the different labeling methods has its advantages and disadvantages, the endoprotease (16)O-to-(18)O catalyzed oxygen exchange at the C-terminal carboxylic acid is extremely promising because of the specificity assured by the enzymatic reaction and the labeling of essentially every protease-derived peptide. We show here that this methodology is applicable to complex biological samples such as a subfraction of human plasma. Furthermore, despite the relatively small mass difference of 4 Da between the two labeled forms, corresponding to the exchange of two oxygen atoms by two (18)O isotopes, it is possible to quantify differentially labeled proteins on an ion trap mass spectrometer with a mass resolution of about 2000 in automated data dependent LC-MS/MS acquisition mode. Post column sample deposition on a MALDI target parallel to on-line ESI-MS/MS enables the analysis of the same compounds by means of ESI- and MALDI-MS/MS. This has the potential to increase the confidence in the quantification results as well as to increase the sequence coverage of potentially interesting proteins by complementary peptide ionization techniques. Additionally the paired y-ion signals in tandem mass spectra of (16)O/(18)O-labeled peptide pairs provide a means to confirm automatic protein identification results or even to assist de novo sequencing of yet unknown proteins.

Experiments in searching small proteins in unannotated large eukaryotic genomes.

There is growing interest to use mass spectrometry data to search genome sequences directly. Previous work by other authors demonstrated that this approach is able to correct and complement available genome annotations. We discuss the practical difficulty of searching large eukaryotic genomes with peptide ion trap tandem mass spectra of small proteins (<40 kDa). The challenging problem of automatically identifying peptides that span across exon/intron boundaries is explored for the first time by using experimental data. In a human genome search, we find that roughly 30% of the peptides are missed, due to various reasons, compared to a Swiss-Prot search. We show that this percentage is significantly reduced with improved parent mass accuracy. We finally provide several examples of predicted gene structures that could be improved by proteomics data, in particular by peptides spanning across exon/intron boundaries.

In vitro and in silico processes to identify differentially expressed proteins.

We present an integrated proteomics platform designed for performing differential analyses. Since reproducible results are essential for comparative studies, we explain how we improved reproducibility at every step of our laboratory processes, e.g. by taking advantage of the powerful laboratory information management system we developed. The differential capacity of our platform is validated by detecting known markers in a real sample and by a spiking experiment. We introduce an innovative two-dimensional (2-D) plot for displaying identification results combined with chromatographic data. This 2-D plot is very convenient for detecting differential proteins. We also adapt standard multivariate statistical techniques to show that peptide identification scores can be used for reliable and sensitive differential studies. The interest of the protein separation approach we generally apply is justified by numerous statistics, complemented by a comparison with a simple shotgun analysis performed on a small volume sample. By introducing an automatic integration step after mass spectrometry data identification, we are able to search numerous databases systematically, including the human genome and expressed sequence tags. Finally, we explain how rigorous data processing can be combined with the work of human experts to set high quality standards, and hence obtain reliable (false positive < 0.35%) and nonredundant protein identifications.