Current peptidomics: Applications, purification, identification, quantification, and functional analysis

Proteomics

Volumn 15, Issue 5-6, 2015, Pages 1026-1038

  Dallas, David C ^a   Guerrero, Andres ^a   Parker, Evan A ^a   Robinson, Randall C ^a   Gan, Junai ^a   German, J Bruce ^a   Barile, Daniela ^a   Lebrilla, Carlito B ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Functional prediction; MS; Peptidomics; Quantitation; Structure prediction; Systems biology

Indexed keywords

BIOLOGICAL MARKER; GLYCOPEPTIDE; NEUROPEPTIDE; PEPTIDE; PROTEIN HYDROLYSATE; PROTEIN PRECURSOR; PEPTIDE FRAGMENT; PROTEIN INTAKE;

ALGORITHM; AMINO ACID SEQUENCE; CELL ORGANELLE; CHEMICAL LABELING; COMPUTER PROGRAM; DATA ANALYSIS; DIGESTION; ELECTROSPRAY MASS SPECTROMETRY; EXTRACTION; FERMENTATION; FOOD PROCESSING; FRACTIONATION; ISOBARIC LABELING; ISOTOPE LABELING; MASS SPECTROMETRY; MATRIX ASSISTED LASER DESORPTION IONIZATION TIME OF FLIGHT MASS SPECTROMETRY; MOLECULAR WEIGHT; MONITORING; PEPTIDE MAPPING; PEPTIDOMICS; PREDICTION; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN FUNCTION; PROTEIN INTAKE; PROTEIN PURIFICATION; PROTEIN SECONDARY STRUCTURE; PROTEIN STRUCTURE; QUADRUPOLE MASS SPECTROMETRY; QUANTITATIVE ANALYSIS; REVIEW; SEQUENCE ANALYSIS; STATISTICAL ANALYSIS; SYSTEMS BIOLOGY; ANIMAL; BOVINE; CHEMISTRY; FOOD ANALYSIS; HUMAN; INFANT; ISOLATION AND PURIFICATION; METABOLISM; PROCEDURES; PROTEIN CONFORMATION; PROTEOMICS;

ANIMALS; BIOMARKERS; CATTLE; DIETARY PROTEINS; DIGESTION; FOOD ANALYSIS; HUMANS; INFANT; MASS SPECTROMETRY; PEPTIDE FRAGMENTS; PROTEIN CONFORMATION; PROTEOMICS; SEQUENCE ANALYSIS, PROTEIN; SYSTEMS BIOLOGY;

EID: 84924723588     PISSN: 16159853     EISSN: 16159861     Source Type: Journal    
DOI: 10.1002/pmic.201400310     Document Type: Review

References (167)

1. Schulte, I., Tammen, H., Selle, H., Schulz-Knappe, P., Peptides in body fluids and tissues as markers of disease. Expert Rev. Mol. Diagn. 2005, 5, 145-157.
2. Dallas, D. C., Underwood, M. A., Zivkovic, A. M., German, J. B., Digestion of protein in premature and term infants. J. Nutr. Disord. Ther. 2012, 2, 1-9.
3. Goldman, A., Garza, C., Schanler, R., Goldblum, R., Molecular forms of lactoferrin in stool and urine from infants fed human milk. Pediatr. Res. 1990, 27, 252-255.
4. Chabance, B., Marteau, P., Rambaud, J., Migliore-Samour, D. et al., Casein peptide release and passage to the blood in humans during digestion of milk or yogurt. Biochimie 1998, 80, 155-165.
5. Dallas, D. C., Guerrero, A., Khaldi, N., Borghese, R. et al., A peptidomic analysis of human milk digestion in the infant stomach reveals protein-specific degradation patterns. J. Nutr. 2014, 144, 815-820.
6. Bouzerzour, K., Morgan, F., Cuinet, I., Bonhomme, C. et al., In vivo digestion of infant formula in piglets: protein digestion kinetics and release of bioactive peptides. Br. J. Nutr. 2012, 1, 1-10.
7. Meisel, H., Frister, H., Chemical characterization of bioactive peptides from in vivo digests of casein. J. Dairy Res. 1989, 56, 343-349.
8. Boutrou, R., Gaudichon, C., Dupont, D., Jardin, J. et al., Sequential release of milk protein-derived bioactive peptides in the jejunum in healthy humans. Am. J. Clin. Nutr. 2013, 97, 1314-1323.
9. Bauchart, C., Morzel, M., Chambon, C., Mirand, P. P. et al., Peptides reproducibly released by in vivo digestion of beef meat and trout flesh in pigs. Br. J. Nutr. 2007, 98, 1187-1195.
10. Umbach, M., Teschemacher, H., Praetorius, K., Hirschhäuser, R. et al., Demonstration of a beta-casomorphin immunoreactive material in the plasma of newborn calves after milk intake. Regul. Pept. 1985, 12, 223-230.
11. Chabance, B., Jollès, P., Izquierdo, C., Mazoyer, E. et al., Characterization of an antithrombotic peptide from alpha-casein in newborn plasma after milk ingestion. Br. J. Nutr. 1995, 73, 583-590.
12. Dallas, D. C., Guerrero, A., Khaldi, N., Castillo, P. A. et al., Extensive in vivo human milk peptidomics reveals specific proteolysis yielding protective antimicrobial peptides. J. Proteome Res. 2013, 12, 2295-2304.
13. Dallas, D. C., Guerrero, A., Parker, E. A., Garay, L. A. et al., Peptidomic profile of milk of Holstein cows at peak lactation. J. Agric. Food Chem. 2013, 62, 58-65.
14. Guerrero, A., Dallas, D. C., Contreras, S., Bhandari, A. et al., Peptidomic analysis of healthy and mastitic bovine milk. Int. Dairy J. 2014, http://dx.doi.org/10.1016/j.idairyj.2014.09.006.
15. Fasano, A., Zonulin and its regulation of intestinal barrier function: the biological door to inflammation, autoimmunity, and cancer. Physiol. Rev. 2011, 91, 151-175.
16. Barbé, F., Le Feunteun, S., Rémond, D., Ménard, O. et al., Tracking the in vivo release of bioactive peptides in the gut during digestion: mass spectrometry peptidomic characterization of effluents collected in the gut of dairy matrix fed mini-pigs. Food Res. Int. 2014, 63, 147-156.
17. Law, B. A., Johnson, M., Technology of Cheesemaking, CRC Press, Boca Raton, FL 1999.
18. McSweeney, P. L., Olson, N. F., Fox, P. F., Healy, A. et al., Proteolytic specificity of chymosin on bovine αs1, -casein. J. Dairy Res. 1993, 60, 401-412.
19. McSweeney, P. L., Olson, N. F., Fox, P. F., Healy, Á., Proteolysis of bovine αS2-casein by chymosin. Z. Lebensm.Unters. Forsch. 1994, 199, 429-432.
20. Møller, K. K., Rattray, F. P., Ardö, Y., Camel and bovine chymosin hydrolysis of bovine αS1-and β-caseins studied by comparative peptide mapping. J. Agric. Food Chem. 2012, 60, 11421-11432.
21. Visser, S., Exterkate, F. A., Slangen, C. J., de Veer, G. J., Comparative study of action of cell wall proteinases from various strains of Streptococcus cremoris on bovine αs1-, β-, and κ-casein. App. Env. Microbiol. 1986, 52, 1162-1166.
22. Fernandez-Espla, M. D., Garault, P., Monnet, V., Rul, F., Streptococcus thermophilus cell wall-anchored proteinase: release, purification, and biochemical and genetic characterization. Appl. Env. Microbiol 2000, 66, 4772-4778.
23. Miclo, L., Roux, E. M., Genay, M., Brusseaux, E. M. et al., Variability of hydrolysis of β-, αs1-, and αs2-caseins by 10 strains of Streptococcus thermophilus and resulting bioactive peptides. J. Agric. Food Chem. 2012, 60, 554-565.
24. Sforza, S., Cavatorta, V., Lambertini, F., Galaverna, G. et al., Cheese peptidomics: a detailed study on the evolution of the oligopeptide fraction in Parmigiano-Reggiano cheese from curd to 24 months of aging. J. Dairy Sci. 2012, 95, 3514-3526.
25. Combes, C., Paterson, E., Amadò, R., Isolation and identification of low-molecular-weight peptides from Emmentaler cheese. J. Food Sci. 2002, 67, 553-559.
26. Toelstede, S., Hofmann, T., Sensomics mapping and identification of the key bitter metabolites in Gouda cheese. J. Agric. Food Chem. 2008, 56, 2795-2804.
27. Gupta, A., Mann, B., Kumar, R., Sangwan, R. B., Identification of antioxidant peptides in cheddar cheese made with adjunct culture Lactobacillus casei ssp. casei 300. Milchwissenschaft 2010, 65, 396-399.
28. Quirós, A., Hernández-Ledesma, B., Ramos, M., Amigo, L. et al., Angiotensin-converting enzyme inhibitory activity of peptides derived from caprine kefir. J. Dairy Sci. 2005, 88, 3480-3487.
29. El-Ghaish, S., Rabesona, H., Choiset, Y., Sitohy, M. et al., Proteolysis by Lactobacillus fermentum IFO3956 isolated from Egyptian milk products decreases immuno-reactivity of αS1-casein. J. Dairy Res. 2011, 78, 203-210.
30. Lisson, M., Lochnit, G., Erhardt, G., Genetic variants of bovine β-and κ-casein result in different immunoglobulin E-binding epitopes after in vitro gastrointestinal digestion. J. Dairy Sci. 2013, 96, 5532-5543.
31. Lisson, M., Lochnit, G., Erhardt, G., In vitro gastrointestinal digestion of bovine alpha-S1 and alpha-S2 casein variants gives rise to different IgE-binding epitopes. Int. Dairy J. 2014, 34, 47-55.
32. Lisson, M., Novak, N., Erhardt, G., Immunoglobulin E epitope mapping by microarray immunoassay reveals differences in immune response to genetic variants of caseins from different ruminant species. J. Dairy Sci. 2014, 97, 1939-1954.
33. Riemenschneider, M., Lautenschlager, N., Wagenpfeil, S., Diehl, J. et al., Cerebrospinal fluid tau and β-amyloid 42 proteins identify Alzheimer disease in subjects with mild cognitive impairment. Arch. Neurol. 2002, 59, 1729-1734.
34. Zürbig, P., Dihazi, H., Metzger, J., Thongboonkerd, V. et al., Urine proteomics in kidney and urogenital diseases: Moving towards clinical applications. Proteomics Clin. Appl. 2011, 5, 256-268.
35. Rossing, K., Mischak, H., Parving, H.-H., Christensen, P. K. et al., Impact of diabetic nephropathy and angiotensin II receptor blockade on urinary polypeptide patterns. Kidney Int. 2005, 68, 193-205.
36. Alkhalaf, A., Zürbig, P., Bakker, S. J. et al., Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy. PLoS One 2010, 5, e13421.
37. Good, D. M., Zürbig, P., Argiles, A., Bauer, H. W. et al., Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease. Mol. Cell Proteomics 2010, 9, 2424-2437.
38. Metzger, J., Kirsch, T., Schiffer, E., Ulger, P. et al., Urinary excretion of twenty peptides forms an early and accurate diagnostic pattern of acute kidney injury. Kidney Int. 2010, 78, 1252-1262.
39. Ling, X. B., Sigdel, T. K., Lau, K., Ying, L. et al., Integrative urinary peptidomics in renal transplantation identifies biomarkers for acute rejection. J. Am. Soc. Nephrol. 2010, 21, 646-653.
40. Sigdel, T. K., Ling, X. B., Lau, K. H., Li, L. et al., Urinary peptidomic analysis identifies potential biomarkers for acute rejection of renal transplantation. Clin. Proteomics 2009, 5, 103-113.
41. Theodorescu, D., Schiffer, E., Bauer, H. W., Douwes, F. et al., Discovery and validation of urinary biomarkers for prostate cancer. Proteomics Clin. Appl. 2008, 2, 556-570.
42. Zimmerli, L. U., Schiffer, E., Zürbig, P., Good, D. M. et al., Urinary proteomic biomarkers in coronary artery disease. Mol. Cell Proteomics 2008, 7, 290-298.
43. Schrader, M., Selle, H., The process chain for peptidomic biomarker discovery. Dis. Markers 2006, 22, 27-37.
44. Tammen, H., Hess, R., in: Bäckvall, H., Lehtiö, J. (Eds.), The Low Molecular Weight Proteome, Springer, New York 2013, pp. 161-168.
45. Ling, X. B., Mellins, E. D., Sylvester, K. G., Cohen, H. J., Urine peptidomics for clinical biomarker discovery. Adv. Clin. Chem. 2010, 51, 181.
46. Diamandis, E. P., Peptidomics for cancer diagnosis: present and future. J. Proteome Res. 2006, 5, 2079-2082.
47. Kolch, W., Neusüß, C., Pelzing, M., Mischak, H., Capillary electrophoresis-mass spectrometry as a powerful tool in clinical diagnosis and biomarker discovery. Mass Spectrom. Rev. 2005, 24, 959-977.
48. Decramer, S., de Peredo, A. G., Breuil, B., Mischak, H. et al., Urine in clinical proteomics. Mol. Cell Proteomics 2008, 7, 1850-1862.
49. Baggerman, G., Verleyen, P., Clynen, E., Huybrechts, J. et al., Peptidomics. J. Chromatogr. B 2004, 803, 3-16.
50. Baggerman, G., Boonen, K., Verleyen, P., De Loof, A. et al., Peptidomic analysis of the larval Drosophila melanogaster central nervous system by two-dimensional capillary liquid chromatography quadrupole time-of-flight mass spectrometry. J. Mass Spectrom. 2005, 40, 250-260.
51. Schoofs, L., Veelaert, D., Vanden Broeck, J. et al., Peptides in the locusts, Locusta migratoria and Schistocerca gregaria. Peptides 1997, 18, 145-156.
52. Schrader, M., Schulz-Knappe, P., Peptidomics technologies for human body fluids. Trends Biotechnol. 2001, 19, S55-S60.
53. Fricker, L. D., Lim, J., Pan, H., Che, F. Y., Peptidomics: identification and quantification of endogenous peptides in neuroendocrine tissues. Mass Spectrom. Rev. 2006, 25, 327-344.
54. Clynen, E., De Loof, A., Schoofs, L., The use of peptidomics in endocrine research. Gen. Comp. Endocr. 2003, 132, 1-9.
55. Hummon, A. B., Amare, A., Sweedler, J. V., Discovering new invertebrate neuropeptides using mass spectrometry. Mass Spectrom. Rev. 2006, 25, 77-98.
56. Slavoff, S. A., Mitchell, A. J., Schwaid, A. G., Cabili, M. N. et al., Peptidomic discovery of short open reading frame-encoded peptides in human cells. Nat. Chem. Biol. 2013, 9, 59-64.
57. Galindo, M. I., Pueyo, J. I., Fouix, S., Bishop, S. A. et al., Peptides encoded by short ORFs control development and define a new eukaryotic gene family. PLoS Biol. 2007, 5, 1052-1062.
58. Fukumoto, H., Tokuda, T., Kasai, T., Ishigami, N. et al., High-molecular-weight β-amyloid oligomers are elevated in cerebrospinal fluid of Alzheimer patients. FASEB J. 2010, 24, 2716-2726.
59. Hortin, G. L., Shen, R.-F., Martin, B. M., Remaley, A. T., Diverse range of small peptides associated with high-density lipoprotein. Biochem. Biophys. Res. Commun. 2006, 340, 909-915.
60. Lahrichi, S. L., Affolter, M., Zolezzi, I. S., Panchaud, A., Food peptidomics: large scale analysis of small bioactive peptides-a pilot study. J Proteomics 2013, 88, 83-91.
61. Hu, L., Li, X., Jiang, X., Zhou, H. et al., Comprehensive peptidome analysis of mouse livers by size exclusion chromatography prefractionation and nanoLC-MS/MS identification. J. Proteome Res. 2007, 6, 801-808.
62. Sigdel, T., Ling, X., Lau, K., Li, L. et al., Urinary peptidomic analysis identifies potential biomarkers for acute rejection of renal transplantation. Clin. Proteomics 2009, 5, 103-113.
63. Hölttä, M., Zetterberg, H., Mirgorodskaya, E., Mattsson, N. et al., Peptidome analysis of cerebrospinal fluid by LC-MALDI MS. PLoS ONE 2012, 7, e42555.
64. Dallas, D. C., Weinborn, V., de Moura Bell, J. M., Wang, M. et al., Comprehensive peptidomic and glycomic evaluation reveals that sweet whey permeate from colostrum is a source of milk protein-derived peptides and oligosaccharides. Food Res. Int. 2014, 63, 203-209.
65. Manes, N. P., Gustin, J. K., Rue, J., Mottaz, H. M. et al., Targeted protein degradation by Salmonella under phagosome-mimicking culture conditions investigated using comparative peptidomics. Mol. Cell Proteomics 2007, 6, 717-727.
66. Khmelnitsky, Y. L., Belova, A. B., Levashov, A. V., Mozhaev, V. V., Relationship between surface hydrophilicity of a protein and its stability against denaturation by organic solvents. FEBS Lett. 1991, 284, 267-269.
67. Tantipaiboonwong, P., Sinchaikul, S., Sriyam, S., Phutrakul, S. et al., Different techniques for urinary protein analysis of normal and lung cancer patients. Proteomics 2005, 5, 1140-1149.
68. Polson, C., Sarkar, P., Incledon, B., Raguvaran, V. et al., Optimization of protein precipitation based upon effectiveness of protein removal and ionization effect in liquid chromatography-tandem mass spectrometry. J. Chromatogr. B 2003, 785, 263-275.
69. Vitorino, R., Barros, A. S., Caseiro, A., Ferreira, R. et al., Evaluation of different extraction procedures for salivary peptide analysis. Talanta 2012, 94, 209-215.
70. Aristoteli, L. P., Molloy, M. P., Baker, M. S., Evaluation of endogenous plasma peptide extraction methods for mass spectrometric biomarker discovery. J. Proteome Res. 2006, 6, 571-581.
71. Thongboonkerd, V., Mcleish, K. R., Arthur, J. M., Klein, J. B., Proteomic analysis of normal human urinary proteins isolated by acetone precipitation or ultracentrifugation. Kidney Int. 2002, 62, 1461-1469.
72. Sivaraman, T., Kumar, T., Jayaraman, G., Yu, C., The mechanism of 2, 2, 2-trichloroacetic acid-induced protein precipitation. J. Protein Chem. 1997, 16, 291-297.
73. Blackstock, W., Trends in automation and mass spectrometry for proteomics. Trends Biotechnol. 2000, 18, 12-17.
74. Yang, H., Wang, X., Liu, X., Wu, J. et al., Antioxidant peptidomics reveals novel skin antioxidant system. Mol. Cell Proteomics 2009, 8, 571-583.
75. Schuchard, M. D., Mehigh, R. J., Cockrill, S. L., Lipscomb, G. T. et al., Artifactual isoform profile modification following treatment of human plasma or serum with protease inhibitor, monitored by 2-dimensional electrophoresis and mass spectrometry. Biotechniques 2005, 39, 239-247.
76. Fukao, Y., Yoshida, M., Kurata, R., Kobayashi, M. et al., Peptide separation methodologies for in-depth proteomics in Arabidopsis. Plant Cell Physiol. 2013, 54, 808-815.
77. Xu, Y., Cao, Q., Svec, F., Fréchet, J. M. J., Porous polymer monolithic column with surface-bound gold nanoparticles for the capture and separation of cysteine-containing peptides. Anal. Chem. 2010, 82, 3352-3358.
78. Liu, T., Qian, W.-J., Strittmatter, E. F., Camp, D. G. et al., High-throughput comparative proteome analysis using a quantitative cysteinyl-peptide enrichment technology. Anal. Chem. 2004, 76, 5345-5353.
79. Foettinger, A., Leitner, A., Lindner, W., Selective enrichment of tryptophan-containing peptides from protein digests employing a reversible derivatization with malondialdehyde and solid-phase capture on hydrazide beads. J. Proteome Res. 2007, 6, 3827-3834.
80. Grunert, T., Pock, K., Buchacher, A., Allmaier, G., Selective solid-phase isolation of methionine-containing peptides and subsequent matrix-assisted laser desorption/ionisation mass spectrometric detection of methionine- and of methionine-sulfoxide-containing peptides. Rapid Commun. Mass Spectrom. 2003, 17, 1815-1824.
81. Thingholm, T. E., Jorgensen, T. J. D., Jensen, O. N., Larsen, M. R., Highly selective enrichment of phosphorylated peptides using titanium dioxide. Nat. Protoc.2006, 1, 1929-1935.
82. Zhang, L., Zhao, Q., Liang, Z., Yang, K. et al., Synthesis of adenosine functionalized metal immobilized magnetic nanoparticles for highly selective and sensitive enrichment of phosphopeptides. Chem. Commun. 2012, 48, 6274-6276.
83. Wada, Y., Tajiri, M., Yoshidas, S., Hydrophilic affinity isolation and MALDI multiple-stage tandem mass spectrometry of glycopeptides for glycoproteomics. Anal. Chem. 2004, 76, 6560-6565.
84. Neue, K., Mormann, M., Peter-Katalinić, J., Pohlentz, G., Elucidation of glycoprotein structures by unspecific proteolysis and direct nanoESI mass spectrometric analysis of ZIC-HILIC-enriched glycopeptides. J. Proteome Res. 2011, 10, 2248-2260.
85. Yu, L., Li, X., Guo, Z., Zhang, X. et al., Hydrophilic interaction chromatography based enrichment of glycopeptides by using Click maltose: a matrix with high selectivity and glycosylation heterogeneity coverage. Chem. Eur. J. 2009, 15, 12618-12626.
86. Liu, L., Yu, M., Zhang, Y., Wang, C. et al., Hydrazide functionalized core-shell magnetic nanocomposites for highly specific enrichment of N-glycopeptides. ACS Appl. Mater. Interfaces 2014, 6, 7823-7832.
87. Kaji, H., Yamauchi, Y., Takahashi, N., Isobe, T., Mass spectrometric identification of N-linked glycopeptides using lectin-mediated affinity capture and glycosylation site-specific stable isotope tagging. Nat. Protoc. 2007, 1, 3019-3027.
88. Cadieux, P. A., Beiko, D. T., Watterson, J. D., Burton, J. P. et al., Surface-enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS): a new proteomic urinary test for patients with urolithiasis. J. Clin. Lab. Anal. 2004, 18, 170-175.
89. Li, L., Sweedler, J. V., Peptides in the brain: mass spectrometry-based measurement approaches and challenges. Annu. Rev. Anal. Chem. 2008, 1, 451-483.
90. Frommberger, M., Zürbig, P., Jantos, J., Krahn, T. et al., Peptidomic analysis of rat urine using capillary electrophoresis coupled to mass spectrometry. Proteomics Clin. Appl. 2007, 1, 650-660.
91. Herrero, M., Ibañez, E., Cifuentes, A., Capillary electrophoresis-electrospray-mass spectrometry in peptide analysis and peptidomics. Electrophoresis 2008, 29, 2148-2160.
92. Shen, Y., Toli, N., Xie, F., Zhao, R. et al., Effectiveness of CID, HCD, and ETD with FT MS/MS for degradomic-peptidomic analysis: comparison of peptide identification methods. J. Proteome Res. 2011, 10, 3929-3943.
93. Boonen, K., Landuyt, B., Baggerman, G., Husson, S. J. et al., Peptidomics: the integrated approach of MS, hyphenated techniques and bioinformatics for neuropeptide analysis. J. Sep. Sci. 2008, 31, 427-445.
94. Seipert, R. R., Dodds, E. D., Clowers, B. H., Beecroft, S. M. et al., Factors that influence fragmentation behavior of N-linked glycopeptide ions. Analyt. Chem. 2008, 80, 3684-3692.
95. Mechref, Y., Use of CID/ETD mass spectrometry to analyze glycopeptides. Curr. Protoc. Protein Sci. 2012, 68, 12.11:12.11.1-12.11.11.
96. Ens, W., Standing, K. G., Matrix-assisted laser desorption/ionization quadrupole time-of-flight mass spectrometry: an elegant tool for peptidomics. Proteomics 2001, 1, 118-131.
97. Caprioli, R. M., Farmer, T. B., Gile, J., Molecular imaging of biological samples: localization of peptides and proteins using MALDI-TOF MS. Analyt. Chem. 1997, 69, 4751-4760.
98. Altelaar, A. F. M., Luxembourg, S. L., McDonnell, L. A., Piersma, S. R. et al., Imaging mass spectrometry at cellular length scales. Nat. Protoc. 2007, 2, 1185-1196.
99. Minerva, L., Boonen, K., Menschaert, G., Landuyt, B. et al., Linking mass spectrometric imaging and traditional peptidomics: a validation in the obese mouse model. Analyt. Chem. 2011, 83, 7682-7691.
100. Bonnel, D., Franck, J., Mériaux, C., Salzet, M. et al., Ionic matrices pre-spotted matrix-assisted laser desorption/ionization plates for patient maker following in course of treatment, drug titration, and MALDI mass spectrometry imaging. Analyt. Biochem. 2013, 434, 187-198.
101. Lemaire, R., Desmons, A., Tabet, J. C., Day, R. et al., Direct analysis and MALDI imaging of formalin-fixed, paraffin-embedded tissue sections. J. Proteome Res. 2007, 6, 1295-1305.
102. Zhang, Z., Jia, C., Li, L., Neuropeptide analysis with liquid chromatography-capillary electrophoresis-mass spectrometric imaging. J. Sep. Sci. 2012, 35, 1779-1784.
103. Verhaert, P. E. M., Pinkse, M. H., Strupat, K., Conaway, M. P., in: Rubakhin, S. S., Sweedler, J. V. (Eds.), Mass Spectrometry Imaging, Humana Press, NY, New York 2010, pp. 433-449.
104. Romanova, E., Lee, J., Kelleher, N., Sweedler, J. et al., Mass spectrometry screening reveals peptides modulated differentially in the medial prefrontal cortex of rats with disparate initial sensitivity to cocaine. AAPS J. 2010, 12, 443-454.
105. Stauber, J., Lemaire, R., Franck, J., Bonnel, D. et al., MALDI imaging of formalin-fixed paraffin-embedded tissues: application to model animals of Parkinson disease for biomarker hunting. J. Proteome Res. 2008, 7, 969-978.
106. Hanrieder, J., Ljungdahl, A., Fälth, M., Mammo, S. E. et al., l-DOPA-induced dyskinesia is associated with regional increase of striatal dynorphin peptides as elucidated by imaging mass spectrometry. Mol. Cell Proteomics 2011, 10, doi:10.1074/mcp.M111.009308.
107. McLean, J. A., Schultz, J. A., Woods, A. S., Ion mobility-mass spectrometry, in: Richard B. Cole (Ed.), Electrospray and MALDI Mass Spectrometry: Fundamentals, Instrumentation, Practicalities, and Biological Applications, Second Edition, John Wiley and Sons, Hoboken, NJ 2010, pp. 411-439.
108. Pringle, S. D., Giles, K., Wildgoose, J. L., Williams, J. P. et al., An investigation of the mobility separation of some peptide and protein ions using a new hybrid quadrupole/travelling wave IMS/oa-ToF instrument. Int. J. Mass Spectrom. 2007, 261, 1-12.
109. Wu, C., Siems, W. F., Klasmeier, J., Hill, H. H., Separation of isomeric peptides using electrospray ionization/high-resolution ion mobility spectrometry. Analyt. Chem. 1999, 72, 391-395.
110. Jia, C., Lietz, C. B., Yu, Q., Li, L., Site-specific characterization of d-amino acid containing peptide epimers by ion mobility spectrometry. Analyt. Chem. 2013, 86, 2972-2981.
111. Ibrahim, Y. M., Shvartsburg, A. A., Smith, R. D., Belov, M. E., Ultrasensitive identification of localization variants of modified peptides using ion mobility spectrometry. Analyt. Chem. 2011, 83, 5617-5623.
112. Shvartsburg, A. A., Zheng, Y., Smith, R. D., Kelleher, N. L., Separation of variant methylated histone tails by differential ion mobility. Analyt. Chem. 2012, 84, 6317-6320.
113. Creese, A. J., Cooper, H. J., Separation and identification of isomeric glycopeptides by high field asymmetric waveform ion mobility spectrometry. Analyt. Chem. 2012, 84, 2597-2601.
114. Kłoniecki, M., Jabłonowska, A., Poznański, J., Langridge, J. et al., Ion mobility separation coupled with MS detects two structural states of Alzheimer's disease Aβ1-40 peptide oligomers. J. Mol. Biol. 2011, 407, 110-124.
115. Old, W. M., Meyer-Arendt, K., Aveline-Wolf, L., Pierce, K. G. et al., Comparison of label-free methods for quantifying human proteins by shotgun proteomics. Mol. Cell Proteomics 2005, 4, 1487-1502.
116. Nanni, P., Levander, F., Roda, G., Caponi, A. et al., A label-free nano-liquid chromatography-mass spectrometry approach for quantitative serum peptidomics in Crohn's disease patients. J. Chromatogr. B 2009, 877, 3127-3136.
117. Ling, X., Lau, K., Deshpande, C., Park, J. et al., Urine peptidomic and targeted plasma protein analyses in the diagnosis and monitoring of Systemic Juvenile Idiopathic Arthritis. Clin. Proteomics 2010, 6, 175-193.
118. Ross, P. L., Huang, Y. N., Marchese, J. N., Williamson, B. et al., Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol. Cell Proteomics 2004, 3, 1154-1169.
119. Thompson, A., Schäfer, J., Kuhn, K., Kienle, S. et al., Tandem Mass Tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Analyt. Chem. 2003, 75, 1895-1904.
120. Menschaert, G., Vandekerckhove, T. T., Baggerman, G., Schoofs, L. et al., Peptidomics coming of age: a review of contributions from a bioinformatics angle. J. Proteome Res. 2010, 9, 2051-2061.
121. Iliuk, A., Galan, J., Tao, W. A., Playing tag with quantitative proteomics. Analyt. Biochem. 2009, 393, 503-513.
122. Bourdetsky, D., Schmelzer, C. E. H., Admon, A., The nature and extent of contributions by defective ribosome products to the HLA peptidome. Proc. Natl. Acad. Sci. U S A 2014, 111, E1591-E1599.
123. Lenco, J., Lan, R., Edwards, N., Goldman, R., MS/MS library facilitated MRM quantification of native peptides prepared by denaturing ultrafiltration. Proteome Sci. 2012, 10, 7.
124. Sano, S., Tagami, S., Hashimoto, Y., Yoshizawa-Kumagaye, K. et al., Absolute quantitation of low abundance plasma APL1β peptides at sub-fmol/mL level by SRM/MRM without immunoaffinity enrichment. J. Proteome Res. 2013, 13, 1012-1020.
125. Araki, Y., Nonaka, D., Tajima, A., Maruyama, M. et al., Quantitative peptidomic analysis by a newly developed one-step direct transfer technology without depletion of major blood proteins: its potential utility for monitoring of pathophysiological status in pregnancy-induced hypertension. Proteomics 2011, 11, 2727-2737.
126. Quintana, L. F., Campistol, J. M., Alcolea, M. P., Bañon-Maneus, E. et al., Application of label-free quantitative peptidomics for the identification of urinary biomarkers of kidney chronic allograft dysfunction. Mol. Cell Proteomics 2009, 8, 1658-1673.
127. Chen, Y.-T., Chen, H.-W., Domanski, D., Smith, D. S. et al., Multiplexed quantification of 63 proteins in human urine by multiple reaction monitoring-based mass spectrometry for discovery of potential bladder cancer biomarkers. J. Proteomics 2012, 75, 3529-3545.
128. Craig, R., Cortens, J. P., Beavis, R. C., Open source system for analyzing, validating, and storing protein identification data. J. Proteome Res. 2004, 3, 1234-1242.
129. Lam, H., Deutsch, E. W., Eddes, J. S., Eng, J. K. et al., Building consensus spectral libraries for peptide identification in proteomics. Nat. Methods 2008, 5, 873-875.
130. Craig, R., Beavis, R. C., TANDEM: matching proteins with tandem mass spectra. Bioinformatics 2004, 20, 1466-1467.
131. Perkins, D. N., Pappin, D. J. C., Creasy, D. M., Cottrell, J. S., Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 1999, 20, 3551-3567.
132. Eng, J. K., McCormack, A. L., Yates III, J. R., An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom. 1994, 5, 976-989.
133. Kim, S., Mischerikow, N., Bandeira, N., Navarro, J. D. et al., The generating function of CID, ETD, and CID/ETD pairs of tandem mass spectra: applications to database search. Mol. Cell Proteomics 2010, 9, 2840-2852.
134. Jiménez, C., Huang, L., Qiu, Y., Burlingame, A., Searching sequence databases over the internet: protein identification using MS-Fit. Curr. Protoc. Protein Sci. 2001, 14, 16.5.1-16.5.6.
135. Geer, L. Y., Markey, S. P., Kowalak, J. A., Wagner, L. et al., Open mass spectrometry search algorithm. J. Proteome Res. 2004, 3, 958-964.
136. Shen, Y., Tolic, N., Hixson, K. K., Purvine, S. O. et al., Proteome-wide identification of proteins and their modifications with decreased ambiguities and improved false discovery rates using unique sequence tags. Analyt. Chem. 2008, 80, 1871-1882.
137. Ma, B., Lajoie, G., Current Protocols in Bioinformatics, John Wiley and Sons, Hoboken, NJ 2009, pp. 13.10. 11-13.10. 18.
138. Frank, A., Pevzner, P., PepNovo: de novo peptide sequencing via probabilistic network modeling. Analyt. Chem. 2005, 77, 964-973.
139. Dancik, V., Addona, T. A., Clauser, K. R., Vath, J. E. et al., De novo peptide sequencing via tandem mass spectrometry. J. Comput. Biol. 1999, 6, 327-342.
140. Tabb, D. L., Ma, Z.-Q., Martin, D. B., Ham, A.-J. L. et al., DirecTag: accurate sequence tags from peptide MS/MS through statistical scoring. J. Proteome Res. 2008, 7, 3838-3846.
141. Clauser, K. R., Baker, P., Burlingame, A. L., Role of accurate mass measurement (±10 ppm) in protein identification strategies employing MS or MS/MS and database searching. Analyt. Chem. 1999, 71, 2871-2882.
142. Searle, B. C., Dasari, S., Wilmarth, P. A., Turner, M. et al., Identification of protein modifications using MS/MS de novo sequencing and the OpenSea alignment algorithm. J. Proteome Res. 2005, 4, 546-554.
143. Dallas, D. C., Martin, W. F., Hua, S., German, J. B., Automated glycopeptide analysis-review of current state and future directions. Brief. Bioinform. 2012, 14, 361-374.
144. Chen, J., Shah, P., Zhang, H., Solid phase extraction of N-linked glycopeptides using hydrazide tip. Analyt. Chem. 2013, 85, 10670-10674.
145. Bandeira, N., Spectral networks: a new approach to de novo discovery of protein sequences and posttranslational modifications. Biotechniques 2007, 42, 687-695.
146. Dasari, S., Chambers, M. C., Codreanu, S. G., Liebler, D. C. et al., Sequence tagging reveals unexpected modifications in toxicoproteomics. Chem. Res. Toxicol. 2011, 24, 204-216.
147. Falkner, J. A., Falkner, J. W., Yocum, A. K., Andrews, P. C., A spectral clustering approach to MS/MS identification of post-translational modifications. J. Proteome Res. 2008, 7, 4614-4622.
148. Bandeira, N., Tsur, D., Frank, A., Pevzner, P. A., Protein identification by spectral networks analysis. Proc. Natl. Acad. Sci. U S A 2007, 104, 6140-6145.
149. Smith, C. A., Want, E. J., O'Maille, G., Abagyan, R. et al., XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Analyt. Chem. 2006, 78, 779-787.
150. Meyrand, M., Dallas, D. C., Caillat, H., Bouvier, F. et al., Comparison of milk oligosaccharides between goats with and without the genetic ability to synthesize αs1-casein. Small Ruminant Res. 2013, 113, 411-420.
151. Sasaki, K., Takahashi, N., Satoh, M., Yamasaki, M. et al., A peptidomics strategy for discovering endogenous bioactive peptides. J. Proteome Res. 2010, 9, 5047-5052.
152. Vijayakumar, V., Guerrero, A., Davey, N., Lebrilla, C. B. et al., EnzymePredictor: a tool for predicting and visualizing enzymatic cleavages of digested proteins. J. Proteome Res. 2012, 11, 6056-6065.
153. Guerrero, A., Dallas, D. C., Contreras, S., Chee, S. et al., Mechanistic peptidomics: factors that dictate specificity in the formation of endogenous peptides in human milk. Mol. Cell Proteomics 2014, Accepted.
154. Klein, J., Eales, J., Zürbig, P., Vlahou, A. et al., Proteasix: A tool for automated and large-scale prediction of proteases involved in naturally occurring peptide generation. Proteomics 2013, 13, 1077-1082.
155. Benedetti, E., X-ray crystallography of peptides: the contributions of the Italian laboratories. Biopolymers 1996, 40, 3-44.
156. Jaroniec, C. P., MacPhee, C. E., Bajaj, V. S., McMahon, M. T. et al., High-resolution molecular structure of a peptide in an amyloid fibril determined by magic angle spinning NMR spectroscopy. Proc. Natl. Acad. Sci. 2004, 101, 711-716.
157. Kaur, H., Garg, A., Raghava, G. P., PEPstr: a de novo method for tertiary structure prediction of small bioactive peptides. Protein Pept. Lett. 2007, 14, 626-631.
158. Maupetit, J., Derreumaux, P., Tuffery, P., PEP-FOLD: an online resource for de novo peptide structure prediction. Nucleic Acids Res. 2009, 37, W498-W503.
159. Thevenet, P., Shen, Y. M., Maupetit, J., Guyon, F. et al., PEP-FOLD: an updated de novo structure prediction server for both linear and disulfide bonded cyclic peptides. Nucleic Acids Res. 2012, 40, W288-W293.
160. Thomas, A., Deshayes, S., Decaffmeyer, M., Van Eyck, M. H. et al., Prediction of peptide structure: How far are we? Proteins: Struct. Funct. Bioinf. 2006, 65, 889-897.
161. Beaufays, J., Lins, L., Thomas, A., Brasseur, R., In silico predictions of 3D structures of linear and cyclic peptides with natural and non-proteinogenic residues. J. Pept. Sci. 2012, 18, 17-24.
162. Clare, D. A., Swaisgood, H. E., Bioactive milk peptides: a prospectus. J. Dairy Sci. 2000, 83, 1187-1195.
163. Fälth, M., Sköld, K., Norrman, M., Svensson, M. et al., SwePep, a database designed for endogenous peptides and mass spectrometry. Mol. Cell Proteomics 2006, 5, 998-1005.
164. Zamyatnin, A. A., Borchikov, A. S., Vladimirov, M. G., Voronina, O. L., The EROP-Moscow oligopeptide database. Nucleic Acids Res. 2006, 34, D261-D266.
165. Liu, F., Baggerman, G., Schoofs, L., Wets, G., The construction of a bioactive peptide database in Metazoa. J. Proteome Res. 2008, 7, 4119-4131.
166. Berdanier, C. D., Dwyer, J. T., Feldman, E. B., Handbook of Nutrition and Food, CRC Press, Boca Raton, FL 2007.
167. Ti, X., Tuzuki, N., Tani, N., Isobe, M. et al., The peptide PIN changes the timing of transitory burst activation of timer-ATPase TIME in accordance with diapause development in eggs of the silkworm, Bombyx mori. J. Insect Physiol. 2005, 51, 1025-1032.