PDF电子书：Gel-Free Proteomics

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6 Z. C$ ]( d# ]  }" \Gel-Free Proteomics) ]' [5 q  K8 D& x# d: E+ G( b
Contents
4 f0 H! E. I) X$ d7 @5 ^Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v0 O9 h  f, S& R4 i$ ?; U
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
0 o1 v* E7 q/ @& D4 B: A1. Mass Spectrometry-Driven Proteomics: An Introduction . . . . . . . . . . . . . 1
7 q' q5 E! @# oKenny Helsens, Lennart Martens, Joël Vandekerckhove,2 t- n6 A. E% \  \8 j6 f( |
and Kris Gevaert
. i: J3 ?+ D* d+ Z2 C: _2. Metabolic Labeling of Model Organisms Using Heavy Nitrogen (15N) . . . . . . 29
. y7 Z& V' E9 K! G/ X4 {Joost W. Gouw, Bastiaan B.J. Tops, and Jeroen Krijgsveld
+ X  R! P+ ?; T+ _/ H3 W. |7 a3. Trypsin-Catalyzed Oxygen-18 Labeling for Quantitative Proteomics . . . . . . . 431 n' x* t7 @1 r  `
Wei-Jun Qian, Brianne O. Petritis, Carrie D. Nicora,
/ [; j, `2 |9 g$ h% aand Richard D. Smith. X, f* k* l8 d6 [
4. ICPL Labeling Strategies for Proteome Research . . . . . . . . . . . . . . . . . 55
+ ^9 U. K/ z) r% Q1 BFriedrich Lottspeich and Josef Kellermann
) i1 e1 J5 [0 Q1 O( Z5. Quantitative Proteome Analysis Using Isobaric Peptide Termini
+ T( C5 D: N; {' I+ ULabeling (IPTL) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65! F; D& F! O2 n8 a4 \+ Y! x, D
Magnus Ø. Arntzen, Christian J. Koehler, Achim Treumann, and Bernd Thiede
& ~, ]! K# `; X# l6. Complete Chemical Modification of Amine and Acid Functional Groups: t1 K- C4 X0 R4 B& M- @
of Peptides and Small Proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . 77. |5 K2 [1 h6 J
Casey J. Krusemark, Brian L. Frey, Lloyd M. Smith, and Peter J. Belshaw
0 U' Z  h4 B# }' P! \0 n2 H/ T7. Production and Use of Stable Isotope-Labeled Proteins for Absolute
1 C3 g! G2 b0 \9 DQuantitative Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93+ }5 @7 C- m8 w  P  o) H
Dorothée Lebert, Alain Dupuis, Jérôme Garin, Christophe Bruley,) j& S1 q( ?! Y3 i
and Virginie Brun& f! P  z$ y1 O9 ^  Y4 ]" r6 y& x
8. Organelle Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
$ S5 W1 Q7 e3 r( o6 y# USophie Duclos and Michel Desjardins7 y7 u2 R# e6 i: f( \! A
9. Membrane Protein Digestion – Comparison of LPI HexaLane
% d2 E* t8 Z7 q5 {5 vwith Traditional Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
1 x+ t" w" e0 ]. APing Sui, Tasso Miliotis, Max Davidson, Roger Karlsson, and Anders Karlsson1 m; j  F( i* }0 A
10. GeLCMS for In-Depth Protein Characterization and Advanced Analysis$ ~) @2 [; E+ O2 `6 t) w
of Proteomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
$ j7 f( \$ Z# t6 i; I; ?5 LAlicia Lundby and Jesper V. Olsen+ P2 y0 `; x$ W* N) X
11. Exploring New Proteome Space: Combining Lys-N Proteolytic Digestion
7 s* c+ ~1 V' eand Strong Cation Exchange (SCX) Separation in Peptide-Centric
9 e4 i6 W& k1 |* ?7 u: d0 \8 iMS-Driven Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
: l* S1 V: B; w% U8 J12. Quantitation of Newly Synthesized Proteins by Pulse Labeling
4 ~5 s0 o! c# y4 d! \with Azidohomoalanine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
! k/ @1 N) l6 b" E# AGertjan Kramer, Piotr T. Kasper, Luitzen de Jong, and Chris G. de Koster0 Z0 R" d! Z1 H- X9 m) E
13. Analytical Strategies in Mass Spectrometry-Based Phosphoproteomics . . . . . . . 183
* G& f) _1 d5 R+ CHeidi Rosenqvist, Juanying Ye, and Ole N. Jensen# d1 U( }0 n8 ~+ z+ q
14. A Protocol on the Use of Titanium Dioxide Chromatography) G. E/ v) q6 x- S# i
for Phosphoproteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215) h% R5 E' [, s$ {
Martijn W.H. Pinkse, Simone Lemeer, and Albert J.R. Heck" K9 }1 \7 p6 V1 Q
15. Positional Proteomics at the N-Terminus as a Means of Proteome Simplification . 2298 i3 }! M% N* `0 \
Gemma R. Davidson, Stuart D. Armstrong, and Robert J. Beynon
% S" \+ T" R* {7 Y% ?! K# B( K7 p$ Z2 ~16. N-Terminomics: A High-Content Screen for Protease Substrates. g7 j/ G, \$ u# z0 F
and Their Cleavage Sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243
  b' U4 Y- k2 l% T( zJohn C. Timmer and Guy S. Salvesen* Y; {+ W7 }  z; P+ ~7 `& Y
17. Protease Specificity Profiling by Tandem Mass Spectrometry Using
, d8 r- g& v3 z+ Q8 u4 _8 VProteome-Derived Peptide Libraries . . . . . . . . . . . . . . . . . . . . . . . . 2578 k8 y% ]' j$ a) s
Oliver Schilling, Ulrich auf dem Keller, and Christopher M. Overall
) q5 v; ]/ `4 f8 I4 m+ L. [18. Identification of Proteolytic Products and Natural Protein N-Termini
4 {0 K2 V7 p! ^$ Pby Terminal Amine Isotopic Labeling of Substrates (TAILS) . . . . . . . . . . . . 273
2 k. G& {7 n4 l: }; m4 F) wAlain Doucet, Oded Kleifeld, Jayachandran N. Kizhakkedathu,
, C9 \- `1 e5 c+ n* }7 m" Fand Christopher M. Overall
1 z0 b; @0 ~4 W7 S4 w" \19. Lectins as Tools to Select for Glycosylated Proteins . . . . . . . . . . . . . . . . 289
$ o! X/ p5 y1 b# N  m- @Els J.M. Van Damme
- m8 \2 D! z1 w9 N4 h' z20. Strong Cation Exchange Chromatography for Analysis of Sialylated Glycopeptides 2997 K1 t8 A" F/ U! |% s( c( ]
Katharina Lohrig, Albert Sickmann, and Urs Lewandrowski
( c+ Z+ J4 T& i& _21. Titanium Dioxide Enrichment of Sialic Acid-Containing Glycopeptides . . . . . . 309- [- W% F( ?4 \! t3 q
Giuseppe Palmisano, Sara E. Lendal, and Martin R. Larsen
2 O6 i1 N9 }4 G- ~6 O' C22. Chemical De-O-glycosylation of Glycoproteins for Applications
% m& ~& p( p: F0 z! K) F9 }% iin LC-Based Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323
2 P! S! N) c+ l* z( ^0 Q& gFranz-Georg Hanisch9 I8 f5 L4 |& |% \5 T7 S
23. Ubiquitination and Degradation of Proteins . . . . . . . . . . . . . . . . . . . . 335) r6 o2 r5 t) x* s  ~: a
Yelena Kravtsova-Ivantsiv and Aaron Ciechanover3 n& ^, m9 G2 d7 R2 P! Y- j1 z8 _
24. Bioinformatics Challenges in Mass Spectrometry-Driven Proteomics . . . . . . . 359
0 R' c7 T/ V. }Lennart Martens' S- r/ a. i# h& V4 y& I
25. A Case Study on the Comparison of Different Software Tools- z% _- J% ~, s2 x2 j- M. U3 z* l
for Automated Quantification of Peptides . . . . . . . . . . . . . . . . . . . . . 373+ ?7 W- ^/ |7 }- }7 `& h
Niklaas Colaert, Joël Vandekerckhove, Lennart Martens,% Y# H5 A  U) F$ r& m
and Kris Gevaert
" }4 p8 Z: _1 Y9 W& g/ A/ g3 ~Subject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399& ]- D0 V6 Z  O- \0 a/ p
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