Targeted degradomics in protein terminomics and protease substrate discovery

References

Agard, N.J., Mahrus, S., Trinidad, J.C., Lynn, A., Burlingame, A.L., and Wells, J.A. (2012). Global kinetic analysis of proteolysis via quantitative targeted proteomics. Proc. Natl. Acad. Sci. USA 109, 1913–1918.10.1073/pnas.1117158109Suche in Google Scholar PubMed PubMed Central

Anderson, N.L., Ptolemy, A.S., and Rifai, N. (2013). The riddle of protein diagnostics: future bleak or bright? Clin. Chem. 59, 194–197.10.1373/clinchem.2012.184705Suche in Google Scholar PubMed

auf dem Keller, U. and Schilling, O. (2010). Proteomic techniques and activity-based probes for the system-wide study of proteolysis. Biochimie 92, 1705–1714.10.1016/j.biochi.2010.04.027Suche in Google Scholar PubMed

Bourmaud, A., Gallien, S., and Domon, B. (2016). Parallel reaction monitoring using quadrupole-orbitrap mass spectrometer: principle and applications. Proteomics 16, 2146–2159.10.1002/pmic.201500543Suche in Google Scholar PubMed

Choi, M., Chang, C.Y., Clough, T., Broudy, D., Killeen, T., MacLean, B., and Vitek, O. (2014). MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments. Bioinformatics 30, 2524–2526.10.1093/bioinformatics/btu305Suche in Google Scholar PubMed

Crawford, E.D., Seaman, J.E., Agard, N., Hsu, G.W., Julien, O., Mahrus, S., Nguyen, H., Shimbo, K., Yoshihara, H.A., Zhuang, M., et al. (2013). The DegraBase: a database of proteolysis in healthy and apoptotic human cells. Mol. Cell. Proteomics 12, 813–824.10.1074/mcp.O112.024372Suche in Google Scholar PubMed PubMed Central

Di Palma, S., Hennrich, M.L., Heck, A.J., and Mohammed, S. (2012). Recent advances in peptide separation by multidimensional liquid chromatography for proteome analysis. J. Proteomics 75, 3791–3813.10.1016/j.jprot.2012.04.033Suche in Google Scholar PubMed

Dix, M.M., Simon, G.M., Wang, C., Okerberg, E., Patricelli, M.P., and Cravatt, B.F. (2012). Functional interplay between caspase cleavage and phosphorylation sculpts the apoptotic proteome. Cell 150, 426–440.10.1016/j.cell.2012.05.040Suche in Google Scholar PubMed PubMed Central

Drag, M. and Salvesen, G.S. (2010). Emerging principles in protease-based drug discovery. Nat. Rev. Drug Discov. 9, 690–701.10.1038/nrd3053Suche in Google Scholar PubMed PubMed Central

Dutta, A., Potier, D.N., Walker, M.J., Gray, O.J., Parker, C., Holland, M., Williamson, A.J., Pierce, A., Unwin, R.D., Krishnan, S., et al. (2016). Development of a selected reaction monitoring mass spectrometry-based assay to detect asparaginyl endopeptidase activity in biological fluids. Oncotarget 7, 70822–70831.10.18632/oncotarget.12224Suche in Google Scholar PubMed PubMed Central

Ebhardt, H.A., Root, A., Sander, C., and Aebersold, R. (2015). Applications of targeted proteomics in systems biology and translational medicine. Proteomics 15, 3193–3208.10.1002/pmic.201500004Suche in Google Scholar PubMed PubMed Central

Eichelbaum, K., Winter, M., Berriel Diaz, M., Herzig, S., and Krijgsveld, J. (2012). Selective enrichment of newly synthesized proteins for quantitative secretome analysis. Nat. Biotechnol. 30, 984–990.10.1038/nbt.2356Suche in Google Scholar PubMed

Fahlman, R.P., Chen, W., and Overall, C.M. (2014). Absolute proteomic quantification of the activity state of proteases and proteolytic cleavages using proteolytic signature peptides and isobaric tags. J. Proteomics 100, 79–91.10.1016/j.jprot.2013.09.006Suche in Google Scholar PubMed

Fortelny, N., Cox, J.H., Kappelhoff, R., Starr, A.E., Lange, P.F., Pavlidis, P., and Overall, C.M. (2014). Network analyses reveal pervasive functional regulation between proteases in the human protease web. PLoS Biol. 12, e1001869.10.1371/journal.pbio.1001869Suche in Google Scholar PubMed PubMed Central

Fortelny, N., Yang, S., Pavlidis, P., Lange, P.F., and Overall, C.M. (2015). Proteome TopFIND 3.0 with TopFINDer and PathFINDer: database and analysis tools for the association of protein termini to pre- and post-translational events. Nucleic Acids Res. 43, D290–D297.10.1093/nar/gku1012Suche in Google Scholar PubMed PubMed Central

Gallien, S., Kim, S.Y., and Domon, B. (2015). Large-scale targeted proteomics using internal standard triggered-parallel reaction monitoring (IS-PRM). Mol. Cell. Proteomics 14, 1630–1644.10.1074/mcp.O114.043968Suche in Google Scholar PubMed PubMed Central

Giansanti, P., Tsiatsiani, L., Low, T.Y., and Heck, A.J. (2016). Six alternative proteases for mass spectrometry-based proteomics beyond trypsin. Nat. Protoc. 11, 993–1006.10.1038/nprot.2016.057Suche in Google Scholar PubMed

Goettig, P. (2016). Effects of glycosylation on the enzymatic activity and mechanisms of proteases. Int. J. Mol. Sci. 17, E1969.10.3390/ijms17121969Suche in Google Scholar PubMed PubMed Central

Hu, S., Loo, J.A., and Wong, D.T. (2006). Human body fluid proteome analysis. Proteomics 6, 6326–6353.10.1002/pmic.200600284Suche in Google Scholar PubMed PubMed Central

Huesgen, P.F., Lange, P.F., and Overall, C.M. (2014). Ensembles of protein termini and specific proteolytic signatures as candidate biomarkers of disease. Proteomics Clin. Appl. 8, 338–350.10.1002/prca.201300104Suche in Google Scholar PubMed

Huesgen, P.F., Lange, P.F., Rogers, L.D., Solis, N., Eckhard, U., Kleifeld, O., Goulas, T., Gomis-Ruth, F.X., and Overall, C.M. (2015). LysargiNase mirrors trypsin for protein C-terminal and methylation-site identification. Nat. Methods 12, 55–58.10.1038/nmeth.3177Suche in Google Scholar PubMed

Igarashi, Y., Eroshkin, A., Gramatikova, S., Gramatikoff, K., Zhang, Y., Smith, J.W., Osterman, A.L., and Godzik, A. (2007). CutDB: a proteolytic event database. Nucleic Acids Res. 35, D546–D549.10.1093/nar/gkl813Suche in Google Scholar PubMed PubMed Central

Julien, O., Zhuang, M., Wiita, A.P., O‘Donoghue, A.J., Knudsen, G.M., Craik, C.S., and Wells, J.A. (2016). Quantitative MS-based enzymology of caspases reveals distinct protein substrate specificities, hierarchies, and cellular roles. Proc. Natl. Acad. Sci. USA 113, E2001–E2010.10.1073/pnas.1524900113Suche in Google Scholar PubMed PubMed Central

Kockmann, T., Trachsel, C., Panse, C., Wahlander, A., Selevsek, N., Grossmann, J., Wolski, W.E., and Schlapbach, R. (2016). Targeted proteomics coming of age - SRM, PRM and DIA performance evaluated from a core facility perspective. Proteomics 16, 2183–2192.10.1002/pmic.201500502Suche in Google Scholar PubMed

Kumar, S., van Raam, B.J., Salvesen, G.S., and Cieplak, P. (2014). Caspase cleavage sites in the human proteome: CaspDB, a database of predicted substrates. PLoS One 9, e110539.10.1371/journal.pone.0110539Suche in Google Scholar PubMed PubMed Central

Kusebauch, U., Campbell, D.S., Deutsch, E.W., Chu, C.S., Spicer, D.A., Brusniak, M.Y., Slagel, J., Sun, Z., Stevens, J., Grimes, B., et al. (2016). Human SRMAtlas: a resource of targeted assays to quantify the complete human proteome. Cell 166, 766–778.10.1016/j.cell.2016.06.041Suche in Google Scholar PubMed PubMed Central

MacLean, B., Tomazela, D.M., Shulman, N., Chambers, M., Finney, G.L., Frewen, B., Kern, R., Tabb, D.L., Liebler, D.C., and MacCoss, M.J. (2010). Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26, 966–968.10.1093/bioinformatics/btq054Suche in Google Scholar PubMed PubMed Central

Marino, G., Eckhard, U., and Overall, C.M. (2015). Protein termini and their modifications revealed by positional proteomics. ACS Chem. Biol. 10, 1754–1764.10.1021/acschembio.5b00189Suche in Google Scholar PubMed

Navarro, P., Kuharev, J., Gillet, L.C., Bernhardt, O.M., MacLean, B., Rost, H.L., Tate, S.A., Tsou, C.C., Reiter, L., Distler, U., et al. (2016). A multicenter study benchmarks software tools for label-free proteome quantification. Nat. Biotechnol. 34, 1130–1136.10.1038/nbt.3685Suche in Google Scholar PubMed PubMed Central

Picotti, P. and Aebersold, R. (2012). Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions. Nat. Methods 9, 555–566.10.1038/nmeth.2015Suche in Google Scholar PubMed

Poli, M., Ori, A., Child, T., Jaroudi, S., Spath, K., Beck, M., and Wells, D. (2015). Characterization and quantification of proteins secreted by single human embryos prior to implantation. EMBO Mol. Med. 7, 1465–1479.10.15252/emmm.201505344Suche in Google Scholar PubMed PubMed Central

Rawlings, N.D., Barrett, A.J., and Finn, R. (2016). Twenty years of the MEROPS database of proteolytic enzymes, their substrates and inhibitors. Nucleic Acids Res. 44, D343–D350.10.1093/nar/gkv1118Suche in Google Scholar PubMed PubMed Central

Rogers, L.D. and Overall, C.M. (2013). Proteolytic post-translational modification of proteins: proteomic tools and methodology. Mol. Cell. Proteomics 12, 3532–3542.10.1074/mcp.M113.031310Suche in Google Scholar PubMed PubMed Central

Rost, H.L., Malmstrom, L., and Aebersold, R. (2015). Reproducible quantitative proteotype data matrices for systems biology. Mol. Biol. Cell 26, 3926–3931.10.1091/mbc.E15-07-0507Suche in Google Scholar PubMed PubMed Central

Sabino, F., Hermes, O., Egli, F.E., Kockmann, T., Schlage, P., Croizat, P., Kizhakkedathu, J.N., Smola, H., and auf dem Keller, U. (2015). In vivo assessment of protease dynamics in cutaneous wound healing by degradomics analysis of porcine wound exudates. Mol. Cell. Proteomics 14, 354–370.10.1074/mcp.M114.043414Suche in Google Scholar PubMed PubMed Central

Schlage, P. and auf dem Keller, U. (2015). Proteomic approaches to uncover MMP function. Matrix Biol. 44–46C, 232–238.10.1016/j.matbio.2015.01.003Suche in Google Scholar PubMed

Shimbo, K., Hsu, G.W., Nguyen, H., Mahrus, S., Trinidad, J.C., Burlingame, A.L., and Wells, J.A. (2012). Quantitative profiling of caspase-cleaved substrates reveals different drug-induced and cell-type patterns in apoptosis. Proc. Natl. Acad. Sci. USA 109, 12432–12437.10.1073/pnas.1208616109Suche in Google Scholar PubMed PubMed Central

Song, J., Tan, H., Boyd, S.E., Shen, H., Mahmood, K., Webb, G.I., Akutsu, T., Whisstock, J.C., and Pike, R.N. (2011). Bioinformatic approaches for predicting substrates of proteases. J. Bioinform. Comput. Biol. 9, 149–178.10.1142/S0219720011005288Suche in Google Scholar

Soste, M., Hrabakova, R., Wanka, S., Melnik, A., Boersema, P., Maiolica, A., Wernas, T., Tognetti, M., von Mering, C., and Picotti, P. (2014). A sentinel protein assay for simultaneously quantifying cellular processes. Nat. Methods 11, 1045–1048.10.1038/nmeth.3101Suche in Google Scholar PubMed

Streng, A.S., de Boer, D., Bouwman, F.G., Mariman, E.C., Scholten, A., van Dieijen-Visser, M.P., and Wodzig, W.K. (2016). Development of a targeted selected ion monitoring assay for the elucidation of protease induced structural changes in cardiac troponin T. J. Proteomics 136, 123–132.10.1016/j.jprot.2015.12.028Suche in Google Scholar PubMed

Tagliabracci, V.S., Engel, J.L., Wiley, S.E., Xiao, J., Gonzalez, D.J., Nidumanda Appaiah, H., Koller, A., Nizet, V., White, K.E., and Dixon, J.E. (2014). Dynamic regulation of FGF23 by Fam20C phosphorylation, GalNAc-T3 glycosylation, and furin proteolysis. Proc. Natl. Acad. Sci. USA 111, 5520–5525.10.1073/pnas.1402218111Suche in Google Scholar PubMed PubMed Central

Turk, B., Turk, D.S.A., and Turk, V. (2012). Protease signalling: the cutting edge. EMBO J. 31, 1630–1643.10.1038/emboj.2012.42Suche in Google Scholar PubMed PubMed Central

Turowec, J.P., Zukowski, S.A., Knight, J.D., Smalley, D.M., Graves, L.M., Johnson, G.L., Li, S.S., Lajoie, G.A., and Litchfield, D.W. (2014). An unbiased proteomic screen reveals caspase cleavage is positively and negatively regulated by substrate phosphorylation. Mol. Cell. Proteomics 13, 1184–1197.10.1074/mcp.M113.037374Suche in Google Scholar PubMed PubMed Central

Wiita, A.P., Hsu, G.W., Lu, C.M., Esensten, J.H., and Wells, J.A. (2014). Circulating proteolytic signatures of chemotherapy-induced cell death in humans discovered by N-terminal labeling. Proc. Natl. Acad. Sci. USA 111, 7594–7599.10.1073/pnas.1405987111Suche in Google Scholar PubMed PubMed Central