CiteULike: neils's phosphopeptides

Immobilized Metal Affinity Chromatography Revisited: pH/Acid Control toward High Selectivity in Phosphoproteomics

Chia-Feng Tsai — 2008-08-16T11:05:46-00:00

J. Proteome Res. (16 August 2008)

Abstract: Despite recent advances in instrumentation and analytical strategies for identification and quantitation of protein phosphorylation, a highly specific enrichment protocol is still a challenge in large-scale studies. Here, we report a simple pH/acid control method that addresses the poor specificity seriously criticized in IMAC. Detailed evaluation of the capture and release mechanism in IMAC revealed that pH, buffer and salt yield a complex interplay in enrichment of phosphopeptides, yet they play individual roles in recovery and specificity. A revised one-step IMAC method with low sample loss and high specificity can be rationally designed by controlling salt, pH and the structure and concentration of organic acid. Without methyl esterification, the one-step IMAC enrichment with single LC-MS/MS identified 386 phosphoproteins in 550 ¼g of non-small-cell lung cancer cell lysate with 96% specificity. Additional fractionation by SDS-PAGE from 4 mg of cell lysate revealed the comprehensive proteome map, identifying 2747 phosphorylation sites from 2360 nondegenerate phosphopeptides and 1219 phosphoproteins with a false discovery rate of 0.63%. To our knowledge, this pH/acid-controlled IMAC procedure provides higher specificity than any other one-step IMAC purification procedure. Furthermore, the simple and reproducible IMAC protocol can be adapted to other solid supports, fully automated or manual, for large-scale identification of the vastly under-explored phosphoproteome.

Colander: A Probability-Based Support Vector Machine Algorithm for Automatic Screening for CID Spectra of Phosphopeptides Prior to Database Search

Bingwen Lu — 2008-06-19T08:09:13-00:00

J. Proteome Res. (19 June 2008)

Abstract: We developed a probability-based machine-learning program, Colander, to identify tandem mass spectra that are highly likely to represent phosphopeptides prior to database search. We identified statistically significant diagnostic features of phosphopeptide tandem mass spectra based on ion trap CID MS/MS experiments. Statistics for the features are calculated from 376 validated phosphopeptide spectra and 376 nonphosphopeptide spectra. A probability-based support vector machine (SVM) program, Colander, was then trained on five selected features. Data sets were assembled both from LC/LC-MS/MS analyses of large-scale phosphopeptide enrichments from proteolyzed cells, tissues and synthetic phosphopeptides. These data sets were used to evaluate the capability of Colander to select pS/pT-containing phosphopeptide tandem mass spectra. When applied to unknown tandem mass spectra, Colander can routinely remove 80% of tandem mass spectra while retaining 95% of phosphopeptide tandem mass spectra. The program significantly reduced computational time spent on database search by 6090%. Furthermore, prefiltering tandem mass spectra representing phosphopeptides can increase the number of phosphopeptide identifications under a predefined false positive rate.

Linear Discriminant Analysis-Based Estimation of the False Discovery Rate for Phosphopeptide Identifications

Xiuxia Du — 2008-04-19T06:48:35-00:00

J. Proteome Res. (19 April 2008)

Abstract: The development of liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has made it possible to characterize phosphopeptides in an increasingly large-scale and high-throughput fashion. However, extracting confident phosphopeptide identifications from the resulting large data sets in a similar high-throughput fashion remains difficult, as does rigorously estimating the false discovery rate (FDR) of a set of phosphopeptide identifications. This article describes a data analysis pipeline designed to address these issues. The first step is to reanalyze phosphopeptide identifications that contain ambiguous assignments for the incorporated phosphate(s) to determine the most likely arrangement of the phosphate(s). The next step is to employ an expectation maximization algorithm to estimate the joint distribution of the peptide scores. A linear discriminant analysis is then performed to determine how to optimally combine peptide scores (in this case, from SEQUEST) into a discriminant score that possesses the maximum discriminating power. Based on this discriminant score, the p- and q-values for each phosphopeptide identification are calculated, and the phosphopeptide identification FDR is then estimated. This data analysis approach was applied to data from a study of irradiated human skin fibroblasts to provide a robust estimate of FDR for phosphopeptides. The Phosphopeptide FDR Estimator software is freely available for download at http://ncrr.pnl.gov/software/.

Online Automated in Vivo Zebrafish Phosphoproteomics: From Large-Scale Analysis Down to a Single Embryo

Simone Lemeer — 2008-02-29T06:46:10-00:00

J. Proteome Res. (29 February 2008)

Abstract: In the developing embryo, as in many other biological processes, complex signaling pathways are under tight control of reversible phosphorylation, guiding cell proliferation, differentiation, and growth. Therefore the large-scale identification of signaling proteins and their post-translational modifications is crucial to understand the proteome biology of the developing zebrafish embryo. Here, we used an automated, robust, and sensitive online TiO2-based LC-MS/MS setup to enrich for phosphorylated peptides from 1 day old zebrafish embryos. We identified, with high confidence, 1067 endogenous phosphorylation sites in a sample taken from 60 embryos (approximately 180 µg), 321 from 10 embryos, and 47 phosphorylation sites from a single embryo, illustrating the sensitivity of the method. This data set, representing by far the largest for zebrafish, was further exploited by searching for serine/threonine or tyrosine kinase motifs using Scansite. For one-third of the identified phosphopeptides a potential kinase motif could be predicted, where it appeared that Cdk5 kinase, p38MAPK, PKA, and Casein Kinase 2 substrates were the most predominant motifs present, underpinning the importance of these kinases in signaling pathways in embryonic development. The phosphopeptide data set was further interrogated using alignments with phosphopeptides identified in recent large-scale phosphoproteomics screens in human and mouse samples. These alignments revealed conservation of phosphorylation sites in several proteins suggesting preserved function in embryonic development.

A dimeric kinase assembly underlying autophosphorylation in the p21 activated kinases.

Michelle Pirruccello — 2007-12-04T03:22:10-00:00

J Mol Biol, Vol. 361, No. 2. (Aug 2006), pp. 312-326.

The p21-activated kinases (PAKs) are serine/threonine kinases that are involved in a wide variety of cellular functions including cytoskeletal motility, apoptosis, and cell cycle regulation. PAKs are inactivated by blockage of the active site of the kinase domain by an N-terminal regulatory domain. GTP-bound forms of Cdc42 and Rac bind to the regulatory domain and displace it, thereby allowing phosphorylation of the kinase domain and maximal activation. A key step in the activation process is the phosphorylation of the activation loop of one PAK kinase domain by another, but little is known about the underlying recognition events that make this phosphorylation specific. We show that the phosphorylated kinase domain of PAK2 dimerizes in solution and that this association is prevented by addition of a substrate peptide. We have identified a crystallographic dimer in a previously determined crystal structure of activated PAK1 in which two kinase domains are arranged face to face and interact through a surface on the large lobe of the kinase domain that is exposed upon release of the auto-inhibitory domain. The crystallographic dimer is suggestive of an engagement that mediates trans-autophosphorylation. Mutations at the predicted dimerization interface block dimerization and reduce the rate of autophosphorylation, supporting the role of this interface in PAK activation.