Because of its availability, ease of collection, and correlation with physiology and pathology, urine is an attractive source for clinical proteomics/peptidomics. However, the lack of comparable data sets from large cohorts has greatly hindered the development of clinical proteomics. Here, we report the establishment of a reproducible, high resolution method for peptidome analysis of naturally occurring human urinary peptides and proteins, ranging from 800 to 17,000 Da, using samples from 3,600 individuals analyzed by capillary electrophoresis coupled to MS. All processed data were deposited in an Structured Query Language (SQL) database. This database currently contains 5,010 relevant unique urinary peptides that serve as a pool of potential classifiers for diagnosis and monitoring of various diseases. As an example, by using this source of information, we were able to define urinary peptide biomarkers for chronic kidney diseases, allowing diagnosis of these diseases with high accuracy. Application of the chronic kidney disease-specific biomarker set to an independent test cohort in the subsequent replication phase resulted in 85.5% sensitivity and 100% specificity. These results indicate the potential usefulness of capillary electrophoresis coupled to MS for clinical applications in the analysis of naturally occurring urinary peptides. Molecular & Cellular Proteomics 9:2424 -2437, 2010.From the Departments of a Chemistry and

We performed a large scale study of electron transfer dissociation (ETD) performance, as compared with ion trap collision-activated dissociation (CAD), for peptides ranging from ϳ1000 to 5000 Da (n ϳ 4000). These data indicate relatively little overlap in peptide identifications between the two methods (ϳ12%). ETD outperformed CAD for all charge states greater than 2; however, regardless of precursor charge a linear decrease in percent fragmentation, as a function of increasing precursor m/z, was observed with ETD fragmentation. We postulate that several precursor cation attributes, including peptide length, charge distribution, and total mass, could be relevant players. To examine these parameters unique ETDidentified peptides were sorted by length, and the ratio of amino acid residues per precursor charge (residues/ charge) was calculated. We observed excellent correlation between the ratio of residues/charge and percent fragmentation. For peptides of a given residue/charge ratio, there is no correlation between peptide mass and percent fragmentation; instead we conclude that the ratio of residues/charge is the main factor in determining a successful ETD outcome. As charge density decreases so does the probability of non-covalent interactions that can bind a newly formed c/z-type ion pair. Recently we have described a supplemental activation approach (ETcaD) to convert these non-dissociative electron transfer product ions to useful c-and z-type ions. Automated implementation of such methods should remove this apparent precursor m/z ceiling. Finally, we evaluated the role of ion density (both anionic and cationic) and reaction duration for an ETD experiment. These data indicate that the best performance is achieved when the ion trap is filled to its space charge limit with anionic reagents. In this largest scale study of ETD to date, ETD continues to show great promise to propel the field of proteomics and, for small-to medium-sized peptides, is highly complementary to ion trap CAD. Electron transfer dissociation (ETD), 1 a relatively new peptide/protein fragmentation method, holds great promise to advance the field of protein mass spectrometry (1-3). As compared with the conventional technique, collision-activated dissociation (CAD), ETD offers a more robust method to characterize post-translational modifications (PTMs) and to interrogate large peptides or even whole proteins (4 -7). Because of these attributes and the fact that it generates c-and z-type products, instead of b-and y-type, many propose that ETD is highly complementary to CAD. ETD reactions, of course, are generally conducted within the confines of ion trap mass spectrometers where sequential CAD and ETD experiments are easily performed. Most proteomics experiments, however, are coupled with on-line chromatographic separations, and analysis time, per peptide, is ideally minimized to increase dynamic range (8). Thus, to extract the most information from a given experiment, knowledge of how these two dissociation techniques complement one another ...

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Owing to its availability, ease of collection, and correlation with pathophysiology of diseases, urine is an attractive source for clinical proteomics. However, many proteomic studies have had only limited clinical impact, due to factors such as modest numbers of subjects, absence of disease controls, small numbers of defined biomarkers, and diversity of analytical platforms. Therefore, it is difficult to merge biomarkers from different studies into a broadly applicable human urinary proteome database. Ideally, the methodology for defining the biomarkers should combine a reasonable analysis time with high resolution, thereby enabling the profiling of adequate samples and recognition of sufficient features to yield robust diagnostic panels. Capillary electrophoresis coupled to mass spectrometry (CE-MS), which was used to analyze urine samples from healthy subjects and patients with various diseases, is a suitable approach for this task. The database of these datasets compiled from the urinary peptides enabled the diagnosis, classification, and monitoring of a wide range of diseases. CE-MS exhibits excellent performance for biomarker discovery and allows subsequent biomarker sequencing independent of the separation platform. This approach may elucidate the pathogenesis of many diseases, and better define especially renal and urological disorders at the molecular level.

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