Binding partner switching on microtubules and aurora-B in the mitosis to cytokinesis transition.

The cytoskeleton globally reorganizes between mitosis (M phase) and cytokinesis (C phase), which presumably requires extensive regulatory changes. To reveal these changes, we undertook a comparative proteomics analysis of cells tightly drug-synchronized in each phase. We identified 25 proteins that bind selectively to microtubules in C phase and identified several novel binding partners including nucleolar and spindle-associated protein. C phase-selective microtubule binding of many of these proteins depended on activity of Aurora kinases as assayed by treatment with the drug VX680. Aurora-B binding partners switched dramatically between M phase to C phase, and we identified several novel C phase-selective Aurora-B binding partners including PRC1, KIF4, and anaphase-promoting complex/cyclosome. Our approach can be extended to other cellular compartments and cell states, and our data provide the first broad biochemical framework for understanding C phase. Concretely, we report a central role for Aurora-B in regulating the C phase cytoskeleton.

Discovery and validation of urine markers of acute pediatric appendicitis using high-accuracy mass spectrometry.

STUDY OBJECTIVE: Molecular definition of disease has been changing all aspects of medical practice, from diagnosis and screening to understanding and treatment. Acute appendicitis is among many human conditions that are complicated by the heterogeneity of clinical presentation and shortage of diagnostic markers. Here, we sought to profile the urine of patients with appendicitis, with the goal of identifying new diagnostic markers. METHODS: Candidate markers were identified from the urine of children with histologically proven appendicitis by using high-accuracy mass spectrometry proteome profiling. These systemic and local markers were used to assess the probability of appendicitis in a blinded, prospective study of children being evaluated for acute abdominal pain in our emergency department. Tests of performance of the markers were evaluated against the pathologic diagnosis and histologic grade of appendicitis. RESULTS: Test performance of 57 identified candidate markers was studied in 67 patients, with median age of 11 years, 37% of whom had appendicitis. Several exhibited favorable diagnostic performance, including calgranulin A (S100-A8), alpha-1-acid glycoprotein 1 (orosomucoid), and leucine-rich alpha-2-glycoprotein (LRG), with the receiver operating characteristic area under the curve and values of 0.84 (95% confidence interval [CI] 0.72 to 0.95), 0.84 (95% CI 0.72 to 0.95), and 0.97 (95% CI 0.93 to 1.0), respectively. LRG was enriched in diseased appendices, and its abundance correlated with severity of appendicitis. CONCLUSION: High-accuracy mass spectrometry urine proteome profiling allowed identification of diagnostic markers of acute appendicitis. Usage of LRG and other identified biomarkers may improve the diagnostic accuracy of clinical evaluations of appendicitis.

When less can yield more - Computational preprocessing of MS/MS spectra for peptide identification.

The effectiveness of database search algorithms, such as Mascot, Sequest and ProteinPilot is limited by the quality of the input spectra: spurious peaks in MS/MS spectra can jeopardize the correct identification of peptides or reduce their score significantly. Consequently, an efficient preprocessing of MS/MS spectra can increase the sensitivity of peptide identification at reduced file sizes and run time without compromising its specificity. We investigate the performance of 25 MS/MS preprocessing methods on various data sets and make software for improved preprocessing of mgf/dta-files freely available from http://hci.iwr.uni-heidelberg.de/mip/proteomics or http://www.childrenshospital.org/research/steenlab.

Urine proteomics for profiling of human disease using high accuracy mass spectrometry.

Knowledge of the biologically relevant components of human tissues has enabled the invention of numerous clinically useful diagnostic tests, as well as non-invasive ways of monitoring disease and its response to treatment. Recent use of advanced MS-based proteomics revealed that the composition of human urine is more complex than anticipated. Here, we extend the current characterization of the human urinary proteome by extensively fractionating urine using ultra-centrifugation, gel electrophoresis, ion exchange and reverse-phase chromatography, effectively reducing mixture complexity while minimizing loss of material. By using high-accuracy mass measurements of the linear ion trap-Orbitrap mass spectrometer and LC-MS/MS of peptides generated from such extensively fractionated specimens, we identified 2362 proteins in routinely collected individual urine specimens, including more than 1000 proteins not described in previous studies. Many of these are biomedically significant molecules, including glomerularly filtered cytokines and shed cell surface molecules, as well as renally and urogenitally produced transporters and structural proteins. Annotation of the identified proteome reveals distinct patterns of enrichment, consistent with previously described specific physiologic mechanisms, including 336 proteins that appear to be expressed by a variety of distal organs and glomerularly filtered from serum. Comparison of the proteomes identified from 12 individual specimens revealed a subset of generally invariant proteins, as well as individually variable ones, suggesting that our approach may be used to study individual differences in age, physiologic state and clinical condition. Consistent with this, annotation of the identified proteome by using machine learning and text mining exposed possible associations with 27 common and more than 500 rare human diseases, establishing a widely useful resource for the study of human pathophysiology and biomarker discovery.

Robust prediction of the MASCOT score for an improved quality assessment in mass spectrometric proteomics.

Protein identification by tandem mass spectrometry is based on the reliable processing of the acquired data. Unfortunately, the generation of a large number of poor quality spectra is commonly observed in LC-MS/MS, and the processing of these mostly noninformative spectra with its associated costs should be avoided. We present a continuous quality score that can be computed very quickly and that can be considered an approximation of the MASCOT score in case of a correct identification. This score can be used to reject low quality spectra prior to database identification, or to draw attention to those spectra that exhibit a (supposedly) high information content, but could not be identified. The proposed quality score can be calibrated automatically on site without the need for a manually generated training set. When this score is turned into a classifier and when features are used that are independent of the instrument, the proposed approach performs equally to previously published classifiers and feature sets and also gives insights into the behavior of the MASCOT score.

Optimizing sample handling for urinary proteomics.

Interrogation of the urinary proteome for clinically useful biomarkers of disease will require normalization of methods for protein extraction and sample handling. Variations in collection methods and other procedures may introduce significant discrepancies in qualitative and quantitative measurements. Here we demonstrate that the method of protein extraction, length of handling at room temperature, and repetitive freeze-thaw cycles do not seem to alter the urinary proteome at either the protein or peptide level in a manner that degrades information obtainable by mass spectrometry.

SALAMI (Spectrum ALignments using high Accuracy Mass and hIgh sensitivity data): how to make the best out of hybrid MS/MS data.

We present a software algorithm that combines ion trap and orbitrap product ion spectra acquired in parallel. The hybrid product ion spectra identify more peptides than when using two separate searches for the orbitrap and LTQ data. The program extracts the high-accuracy mass data from the Orbitrap mass analyzer and combines it with the high-sensitivity data analyzed in the LTQ linear ion trap; the m/z values of the high-confidence fragment ions are corrected to orbitrap mass accuracies and the fragment ion intensities are amplified. This approach utilizes the parallel spectrum measurement capabilities of the LTQ-Orbitrap. We present our approach to handling this type of hybrid data, explain our alignment program, and discuss the advantages of the chosen methodology.

Temporal variations of the postnatal rat urinary proteome as a reflection of systemic maturation.

The rat kidney matures during the first 2 wk of life, suggesting that temporal variations in the urinary proteome may occur during this period. We describe the urine proteome during postnatal development in the rat and demonstrate specific proteomic changes corresponding to developmental milestones. Urine was collected from 30 rats at five postnatal (P) days of life (P1, P3, P7, P14, and >P30) by bladder aspiration. The proteome was assessed by nano-ESI-LC-MS/MS. For identification, we used stringent criteria to provide a 1% false positive rate at the peptide level. The proteins in common at each time interval decreased during postnatal maturation. When comparing all five developmental times, six proteins were ubiquitously present. We detected 14 proteins involved with cellular adhesion, structure, or proliferation and differentiation only during neonatal development. Additionally, 30 proteins were specific to adults, of which 13 originated from the prostate or seminal vesicle. This is the first MS characterization of the normal urinary proteome in early postnatal rodent development that demonstrates distinct differences correlating with different stages of tissue maturation. Further characterization of the normal urinary proteome may provide the basis for identification of urinary biomarkers of diseases of the urinary tract.

Protein sulfation analysis--A primer.

The aim of this review is to present an overview of protein sulfation in the context of 'modificomics', i.e. post-translational modification-specific proteome research. In addition to a short introduction to the biology of protein sulfation (part 1), we will provide detailed discussion regarding (i) methods and tools for prediction of protein tyrosine sulfation sites (part 2), (ii) biochemical techniques used for protein sulfation analysis (part 3.1), and (iii) mass spectrometric strategies and methods applied to protein sulfation analysis (part 3.2). We will highlight strengths and limitations of different strategies and approaches (including references), providing a primer for newcomers to protein sulfation analysis.

Algorithm for accurate similarity measurements of peptide mass fingerprints and its application.

We present a simple algorithm which allows accurate estimates of the similarity between peptide fingerprint mass spectra from matrix assisted laser desorption/ionization (MALDI) spectrometers. The algorithm, which is a combination of mass correlation and intensity rank correlation, was used to cluster similar spectra and to generate consensus spectra from a data store of more than 100,000 spectra. The resulting first spectra library of 1248 unambiguously identified different protein digests was used to search for missed cleavage patterns that have not been reported so far and to shed light on some peptide ionization characteristics. The findings of this study could be directly implemented in peptide mass fingerprint search algorithms to decrease the false positive error rate to <0.25%. Furthermore, the results contribute to the understanding of the peptide ionization process in MALDI experiments.

The Sulfinator: predicting tyrosine sulfation sites in protein sequences.

UNLABELLED: Protein tyrosine sulfation is an important post-translational modification of proteins that go through the secretory pathway. No clear-cut acceptor motif can be defined that allows the prediction of tyrosine sulfation sites in polypeptide chains. The Sulfinator is a software tool that can be used to predict tyrosine sulfation sites in protein sequences with an overall accuracy of 98%. Four different Hidden Markov Models were constructed, each of them specialized to recognize sulfated tyrosine residues depending on their location within the sequence: near the N-terminus, near the C-terminus, in the center of a window with a size of at least 25 amino acids, as well as in windows containing several tyrosine residues. AVAILABILITY: The Sulfinator is accessible at (http://www.expasy.org/tools/sulfinator/). SUPPLEMENTARY INFORMATION: Sulfinator documentation is accessible at (http://www.expasy.org/tools/sulfinator/sulfinator-doc.html).