Mining Phosphopeptide Signals in Liquid Chromatography−Mass Spectrometry Data for Protein Phosphorylation Analysis

Wu, Hsin‐Yi; Tseng, Vincent S.; Liao, Pao‐Chi

doi:10.1021/pr060631d

Cited by 27 publications

(34 citation statements)

References 51 publications

(104 reference statements)

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“…Yet it has been demonstrated that some peptides remain undetected in positive ion mode MS possibly due to their multiple phosphorylation. Hence to obtain the most complete coverage of all phosphopeptides in the sample, several groups have recently shown that treating the enriched mixture with AP reveals the presence of a high number of phosphopeptides (15)(16)(17)30). One major drawback of the AP approach is that no information on the location of the phosphorylated site is revealed, a limitation that is even more evident when more than one potential residue is present.…”

Section: Discussionmentioning

confidence: 99%

“…Evaluation of Alkaline Phosphatase Treatment-Many methods have been used in the past to confirm the presence of phosphorylation on a protein of interest (12,13,(15)(16)(17). Dephosphorylation of the phosphopeptide is the most straightforward and specific approach to confirm phosphorylation of the cognate peptide.…”

Section: Evaluation Of Phosphopeptide Enrichment Methods-largementioning

confidence: 99%

“…However, large scale analysis of phosphotyrosine using specific antibodies commercially available can be relatively expensive and would not provide any information on serine and threonine phosphorylation. Another strategy adapted recently identified phosphopeptides in a sample using alkaline phosphatase (AP) treatment applicable to all hydroxyamino acids, even tyrosine residues (15)(16)(17). The major drawback from the AP approach is that the information of the phosphorylation site on the peptide is lost.…”

Section: Molecular and Cellular Proteomics 7: 645-660 2008mentioning

confidence: 99%

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Combined Enzymatic and Data Mining Approaches for Comprehensive Phosphoproteome Analyses

Marcantonio

Trost

Courcelles

et al. 2008

Molecular & Cellular Proteomics

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Protein phosphorylation is a central cell signaling event that underlies a broad spectrum of key physiological processes. Advances in affinity chromatography and mass spectrometry are now providing the ability to identify and quantitate thousands of phosphorylation sites simultaneously. Comprehensive phosphoproteome analyses present sizable analytical challenges in view of suppression effects of phosphopeptides and the variable quality of MS/MS spectra. This work presents an integrated enzymatic and data mining approach enabling the comprehensive detection of native and putative phosphopeptides following alkaline phosphatase digestion of titanium dioxide (TiO 2 )-enriched cell extracts. The correlation of retention times of more than 750 phospho-and dephosphopeptide pairs from J774 macrophage cell extracts indicated that removal of the phosphate groups can impart a gain or a loss in hydrophobicity that is partly explained by the formation of a salt bridge with proximal amino groups. Dephosphorylation also led to an average 2-fold increase in MS sensitivity that facilitated peptide sequencing. More importantly, alkaline phosphatase digestion enhanced the overall population of putative phosphopeptides from TiO 2 -enriched cell extracts providing a unique approach to profile multiphosphorylated cognates that would have remained otherwise undetected. The application of this approach is demonstrated for differential phosphoproteome analyses of mouse macrophages exposed to interferon-␥ for 5 min. TiO 2 enrichment enabled the identification of 1143 phosphopeptides from 432 different proteins of which 125 phosphopeptides showed a 2-fold change upon interferon-␥ exposure. The use of alkaline phosphatase nearly doubled the number of putative phosphopeptides assignments leading to the observation of key interferon-␥ signaling events involved in vesicle traf-

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Section: Discussionmentioning

confidence: 99%

Section: Evaluation Of Phosphopeptide Enrichment Methods-largementioning

confidence: 99%

Section: Molecular and Cellular Proteomics 7: 645-660 2008mentioning

confidence: 99%

See 1 more Smart Citation

Combined Enzymatic and Data Mining Approaches for Comprehensive Phosphoproteome Analyses

Marcantonio

Trost

Courcelles

et al. 2008

Molecular & Cellular Proteomics

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“…From previous literature studies, it is known that the pH of the binding and elution buffer are important conditions in TiO 2 -based phosphopeptide enrichment [25,37,38]. The experiments were evaluated with loading and elution solutions of different pH to optimize the TiO 2 -based enrichment of phosphopeptides.…”

Section: Assessment Of Tio2 Micro-column Enrichment For Standard Phosmentioning

confidence: 99%

Optimization of titanium dioxide and immunoaffinity-based enrichment procedures for tyrosine phosphopeptide using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

2014

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Tyrosine phosphorylation is an important regulator of signaling in cellular pathways, and dysregulated tyrosine phosphorylation causes several diseases. Mass spectrometry has revealed the importance of global phosphoproteomic characterization. Analysis of tyrosine phosphorylation by studying the mass-spectrometry (MS)-determined phosphoproteome remains difficult because of the relatively low abundance of tyrosine phosphoproteins. To effectively evaluate tyrosine-phosphopeptide enrichment and reduce ion suppression from non-phosphorylated peptides in MS analysis, three trypsin-digested BSA peptides and 14 standard phosphopeptides, including six tyrosine phosphopeptides, four serine phosphopeptides, and four threonine phosphopeptides, were subjected to titanium dioxide immunoaffinity-based enrichment and also to combined enrichment using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and liquid chromatography-mass spectrometry (LC-MS) analyses. The enrichment factors were evaluated to determine the efficiency of each enrichment procedure. Comparison of five optimized enrichment methods, including TiO2-based immunoaffinity purification in Tris and MOPS buffer systems, TiO2-immunoaffinity enrichment, and immunoaffinity-TiO2 enrichment for total tyrosine, serine and threonine phosphopeptides, revealed that the order of the enrichment factors for total tyrosine phosphopeptides is: (i) immunoaffinity-TiO2 (enrichment factor = 38,244), (ii) TiO2-immunoaffinity (enrichment factor = 24,987), (iii) TiO2 micro-column (enrichment factor = 10,305), (iv) immunoaffinity in Tris buffer system (enrichment factor = 1450), and (v) immunoaffinity in the MOPS buffer system (enrichment factor = 32). These results reveal that an alternative enrichment scheme before use of a TiO2 micro-column, using immunoaffinity 4G10 and PY99 antibody enrichment under optimized conditions, can provide greater selectivity for tyrosine-phosphopeptide enrichment.

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“…Di-(2-ethylhexyl) phthalate (DEHP) with a wide range of metabolites, including mono-(2-ethyl-hexyl) phthalate (MEHP), mono-(2-ethyl-hydroxyhexyl) phthalates (OHMEHPs), mono-(2-ethyl-oxohexyl) phthalates (oxo-MEHPs), and mono-(2-ethyl-carboxypentyl) phthalates (cx-MEPPs), has been reported [9][10][11]. To illustrate the effectiveness of the proposed procedure for detecting metabolite signals within LC-MS data, DEHP was used as a model compound.…”

mentioning

confidence: 99%

A statistical procedure to selectively detect metabolite signals in LC-MS data based on using variable isotope ratios

Lin

Tseng

et al. 2010

J. Am. Soc. Mass Spectrom.

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The tracing of metabolite signals in LC-MS data using stable isotope-labeled compounds has been described in the literature. However, the filtering efficiency and confidence when mining metabolite signals in complex LC-MS datasets can be improved. Here, we propose an additional statistical procedure to increase the compound-derived signal mining efficiency. This method also provides a highly confident approach to screen out metabolite signals because the correlation of varying concentration ratios of native/stable isotope-labeled compounds and their instrumental response ratio is used. An in-house computational program [signal mining algorithm with isotope tracing (SMAIT)] was developed to perform the statistical procedure. To illustrate the SMAIT concept and its effectiveness for mining metabolite signals in LC-MS data, the plasticizer, di-(2-ethylhexyl) phthalate (DEHP), was used as an example. The statistical procedure effectively filtered 15 probable metabolite signals from 3617 peaks in the LC-MS data. These probable metabolite signals were considered structurally related to DEHP. Results obtained here suggest that the statistical procedure could be used to confidently facilitate the detection of probable metabolites from a compoundderived precursor presented in a complex LC-MS dataset. One strategy to mine MS data for metabolite signals uses the isotope cluster that is formed after treating test subjects with an equal mixture of native and isotopelabeled compounds [1][2][3]. In mineral metabolism research, the stable isotope ratio (1:1) from spiked native and isotope-labeled compounds has been used for metabolite signal detection. The equal response signatures of signal doublets were traced [4]. A strategy using the stable isotope-labeled tracing concept has been developed to detect reactive metabolites, such as glutathioneconjugated metabolites [5].Another report has demonstrated that equal amounts of native and stable isotope-labeled compounds can be used to detect untargeted metabolite signals with particular isotopic ratios in LC-MS data, where this work also demonstrated the use of a computational program, DoGEX, to facilitate the signal mining process [6]. The program detects the metabolite signals according to a particular stable isotope ratio and mass difference after data alignment, noise removal, baseline correction, peak detection, and spectral filtering processes. Additionally, the program requires a user-defined isotopic ratio of native to isotopelabeled signal responses to define metabolite signals. However, the isotopic ratios of metabolite signals from equal amounts of spiked native and isotope-labeled compounds are not always closed to 1 because of the influences from analytical variations of sample preparation, instrumental analysis, and matrix interference. This is especially true when signal doublet responses are low [7]. Setting acceptable tolerance for wanted ratios is still empirical, which results in the challenges while tracing one specific ratio [8].We propose, herein, an addition...

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Mining Phosphopeptide Signals in Liquid Chromatography−Mass Spectrometry Data for Protein Phosphorylation Analysis

Cited by 27 publications

References 51 publications

Combined Enzymatic and Data Mining Approaches for Comprehensive Phosphoproteome Analyses

Combined Enzymatic and Data Mining Approaches for Comprehensive Phosphoproteome Analyses

Optimization of titanium dioxide and immunoaffinity-based enrichment procedures for tyrosine phosphopeptide using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

A statistical procedure to selectively detect metabolite signals in LC-MS data based on using variable isotope ratios

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