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Review
. 2016 Jan 5;88(1):74-94.
doi: 10.1021/acs.analchem.5b04123. Epub 2015 Nov 19.

Phosphoproteomics in the Age of Rapid and Deep Proteome Profiling

Nicholas M Riley  1   2 , Joshua J Coon  1   2   3
Affiliations
Review

Phosphoproteomics in the Age of Rapid and Deep Proteome Profiling

Nicholas M Riley et al. Anal Chem. .
No abstract available

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1
Figure 1
Typical phosphoproteomic workflow. Each step in a phosphoproteomic experiment can contribute to limitations in reproducibility and phosphoproteomic depth, which can ultimately restrict the biological insight obtained from an experiment. Concerted efforts in the phosphoproteomics community to improve each step in this workflow continue to advance our ability to sample the phosphoproteome with greater speed and depth, but comprehensive phosphoproteome coverage remains out of reach.
Figure 2
Figure 2
Phosphoproteomics using complementary proteases. Phosphosite intensities correlate strongly (r > 0.8, yellow) when data sets are obtained following digestion with the same protease but correlation between data sets originating from different proteases is low (r ∼ 0.25–0.55, blue). This difference indicates that using multiple proteases provides access to different regions of the phosphoproteome. Reprinted with permission from Giansanti, P.; Aye, T. T.; van den Toorn, H.; Peng, M.; van Breukelen, B.; Heck, A. J. R. Cell Rep.2015, 11, 1834–1843 (ref (27)). Copyright 2015 Cell Press.
Figure 3
Figure 3
Examining enrichment biases between Ti4+-IMAC and TiOx. Frequency plots show physiochemical characteristics of a phosphopeptide library (∼23 000 phosphopeptides) that was analyzed via direct analysis (orange), Ti4+-IMAC enrichment (blue), and TiOx enrichment (green). No major differences between the enrichment strategies are evident when considering phosphopeptide length (A), relative position of the phosphosite (B), number of basic or acidic residues in the −1 to +1 position of the phosphosite (C and D, respectively), calculated isoelectric point of the phosphopeptides (E), or calculated Gravy hydropathy index (F). When considering replicate Ti4+-IMAC and TiOx enrichments in HeLa cells (G), overlap between replicates of the same method is not superb (requiring ∼4–5 replicates to approach asymptotical gains), but good phosphoproteomic depth can be achieved by batching replicate measurements. Combining replicate enrichments from the two methods also boosts phosphosite identification. Reprinted with permission from Matheron, L.; van den Toorn, H.; Heck, A. J. R.; Mohammed, S. Anal. Chem.2014, 86, 8312–8320 (ref (37)). Copyright 2015 American Chemical Society.
Figure 4
Figure 4
Fractionation of phosphopeptides with high pH RPLC. The comparison of high pH RPLC and SCX offline fractionation (A) shows that the two methods identify many of the same phosphosites, but high pH RPLC provides nearly 10 000 additional sites. Through further optimization, high pH RPLC provided 27 712 localized phosphosites in three replicate measurements (B). The number of confidently localized phosphosites (C and D) demonstrates the superior performance of an optimized high pH RPLC for phosphopeptide fractionation. Reprinted with permission from Batth, T. S.; Francavilla, C.; Olsen, J. V. J. Proteome Res.2014, 13, 6176–6186 (ref (61)). Copyright 2015 American Chemical Society.
Figure 5
Figure 5
Properties of the HeLa cell phosphoproteome. Label-free quantitative proteomics provided dynamic range measurements for >38 000 phosphosites in the human phosphoproteome. The left panel of part A shows a histogram of phosphopeptide abundances overlaid with intensity rank order (red line, lowest to highest intensity) of the phosphopeptides. The right panel shows the distribution of cumulative phosphopeptide abundance and indicates that a significant portion of total phosphopeptide intensity comes from a few thousand phosphopeptides. The majority of phosphoproteins have five or fewer phosphosites (B, left), and the relationship between protein abundance and its number of phosphosites is displayed in the right panel of part B. The majority of phosphosites are phosphoserine (pS), followed by phosphothreonine (pT), left panel of part C. The number of phosphotyrosine (pY) sites can be increased through immunoprecipitation strategies, but the enrichment strategy used affects the observed intensity, left and center of part C. The right panel of part C shows the distribution of known and novel phosphosites compared to the PhosphoSitePlus database. Reprinted with permission from Sharma, K.; D’Souza, R. C. J.; Tyanova, S.; Schaab, C.; Wiśniewski, J. R.; Cox, J.; Mann, M. Cell Rep.2014, 8, 1583–1594 (ref (96)). Copyright 2015 Cell Press.
Figure 6
Figure 6
Quantitative strategies for global phosphoproteomics. MS1 quantitation is a popular approach because measurements of phosphopeptides across their elution profiles provide accurate quantitative information. Label-free quantitation requires no additional steps in the phosphoproteomic workflow, and samples are analyzed individually. Quantitation is then performed across separate LC–MS/MS analyses using accurate mass and retention time windows to compare phosphopeptides from different samples. In contrast, stable isotope labeling methods permit multiplexing, where multiple samples can be mixed after labeling and then analyzed in the same LC–MS/MS analysis. In metabolic labeling, e.g., SILAC, stable isotopes are incorporated into samples during growth on a defined medium. Phosphopeptides from different samples vary in mass based on the incorporated isotopes, which can be seen by mass shifts in the MS1. Areas under the elution curve for the corresponding light and heavy phosphopeptides can then be compared for quantitative information. Chemical labeling (dimethyl, mTRAQ) works via the same mechanism, except that the mass shifts are achieved through a chemical label that is reactive with peptide functional groups (e.g., primary amines), rather than incorporation in growth media. Isobaric labeling also uses a reactive tag that labels peptide functional groups, but quantitation is achieved at the MS2 level. The intact mass of each label is the same based on the coupling of reporter and balance regions that have an equivalent number of total heavy isotopes. Upon phosphopeptide dissociation, the reporter ions fragment off, allowing comparison of relative reporter ion intensities for quantitative measurements between samples, all within the same scan that provides phosphopeptide identification.
Figure 7
Figure 7
Cross section of recent phosphoproteomic literature. This graphic shows relevant information for 30 recent and impactful phosphoproteomic methodology publications. Although not comprehensive, it gives a snapshot of popular methods in current studies. General details about the biological system, enrichment method, fractionation approach, quantitative strategy, and number of phosphosites characterized are provided. The number of phosphosites reported here represents what was reported as confidently localized and quantified by each manuscript. An asterisk (*) indicates that localization confidence was not reported, and an octothorpe (#) indicates other PTMs were also enriched in the study. Some publications did not report quantitative information.
Figure 8
Figure 8
Phosphosite localization. The workflow here shows the localization steps taken by phosphoRS, but the concepts are valid for a variety of localization algorithms. MS/MS spectra are binned into windows (A) and the optimal peak depth to use for localization is determined by calculating cumulative binomial probabilities for each isoform (B). Potential phosphopeptide isoforms are scored based on the optimal number of most intense peaks from each m/z window (C), and sequence and phosphosite probabilities are calculated (D). Reprinted with permission from Taus, T.; Köcher, T.; Pichler, P.; Paschke, C.; Schmidt, A.; Henrich, C.; Mechtler, K. J. Proteome Res.2011, 10, 5354–5362 (ref (197)). Copyright 2015 American Chemical Society.
Figure 9
Figure 9
Interaction networks built from a phosphosite-centric perspective. PhosphoPath is a Cytoscape-based tool that aids visualization and analysis of quantitative phosphoproteomic data. Displayed here is a quantitative interaction network of members of the MAPK pathway, with blue and red representing down- and up-regulation, respectively. Straight lines show protein–protein interactions from Biogrid while arrows visualize kinase-substrate interactions from PhosphoSitePlus. Multiplicity is indicated by the color bar for each protein, and edges can be added manually, such as the red edge at the top of the figure showing inhibition of NF1 on NRAS. Reprinted with permission from Raaijmakers, L. M.; Giansanti, P.; Possik, P. A.; Mueller, J.; Peeper, D. S.; Heck, A. J. R.; Altelaar, A. F. M. J. Proteome Res.2015 (ref (213)). Copyright 2015 American Chemical Society.
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References

    1. Cohen P. Eur. J. Biochem. 2001, 268, 5001–5010. 10.1046/j.0014-2956.2001.02473.x. - DOI - PubMed
    1. Thorner J.; Hunter T.; Cantley L. C.; Sever R. Cold Spring Harbor Perspect. Biol. 2014, 6, a022913. 10.1101/cshperspect.a022913. - DOI - PMC - PubMed
    1. Johnson L. N. Biochem. Soc. Trans. 2009, 37, 627–641. 10.1042/BST0370627. - DOI - PubMed
    1. Manning G.; Plowman G. D.; Hunter T.; Sudarsanam S. Trends Biochem. Sci. 2002, 27, 514–520. 10.1016/S0968-0004(02)02179-5. - DOI - PubMed
    1. Moorhead G. B. G.; De Wever V.; Templeton G.; Kerk D. Biochem. J. 2009, 417, 401–409. 10.1042/BJ20081986. - DOI - PubMed

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