PDF电子书：Gel-Free Proteomics

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7 ~. t* c! m! wGel-Free Proteomics! E1 `) n+ y+ M% T$ c/ l
Contents7 X0 d9 ?4 j# l& _* }2 y1 _, I
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v( w3 E1 T  V; ?  O% U
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix8 ?6 v' f1 P: i) S3 H9 {" _2 U- H
1. Mass Spectrometry-Driven Proteomics: An Introduction . . . . . . . . . . . . . 10 ^5 J2 l# i7 s! H8 j3 ]
Kenny Helsens, Lennart Martens, Joël Vandekerckhove,
% h4 f8 s* v, P( X7 s9 E) g5 mand Kris Gevaert, w8 Q: T0 |4 b+ ]) m
2. Metabolic Labeling of Model Organisms Using Heavy Nitrogen (15N) . . . . . . 290 B, H9 e  s) V1 }4 A
Joost W. Gouw, Bastiaan B.J. Tops, and Jeroen Krijgsveld
$ t( m7 \6 l' F% b3. Trypsin-Catalyzed Oxygen-18 Labeling for Quantitative Proteomics . . . . . . . 43
% p/ m; u9 _2 e" M8 QWei-Jun Qian, Brianne O. Petritis, Carrie D. Nicora,
+ h6 a- Z' R( D! W0 Y: uand Richard D. Smith4 B: c+ l( \2 J2 W; [
4. ICPL Labeling Strategies for Proteome Research . . . . . . . . . . . . . . . . . 55  e- R% G8 p: n1 S. o
Friedrich Lottspeich and Josef Kellermann: I5 W# |, ~/ Z+ h
5. Quantitative Proteome Analysis Using Isobaric Peptide Termini/ L0 M+ a+ s4 W; w  R& p
Labeling (IPTL) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65  s1 d$ o# M  w' p) i- A
Magnus Ø. Arntzen, Christian J. Koehler, Achim Treumann, and Bernd Thiede- H3 E0 W; ?; L# M1 u
6. Complete Chemical Modification of Amine and Acid Functional Groups
  E" V- o" w; _( Rof Peptides and Small Proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
8 w7 \4 F1 t/ cCasey J. Krusemark, Brian L. Frey, Lloyd M. Smith, and Peter J. Belshaw. W3 t4 w7 ~, e5 d/ L
7. Production and Use of Stable Isotope-Labeled Proteins for Absolute
/ E( d+ m3 f) c! d1 GQuantitative Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
* D5 [: [9 g0 _8 y* y8 i7 }Dorothée Lebert, Alain Dupuis, Jérôme Garin, Christophe Bruley,
1 D" a# y' s6 ?( Q3 y: C& Aand Virginie Brun
. C9 N6 Q2 f3 d0 d; ^; c8. Organelle Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117) L& d5 O! I6 y% ~; j1 `6 \
Sophie Duclos and Michel Desjardins
. ?( ?2 c7 c2 y/ }9. Membrane Protein Digestion – Comparison of LPI HexaLane1 Y; b& }* s, s% X9 F$ C
with Traditional Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129: `! z' N3 E# u. k6 a
Ping Sui, Tasso Miliotis, Max Davidson, Roger Karlsson, and Anders Karlsson
. K" F( \- ~. w3 p  m) Q: `$ v10. GeLCMS for In-Depth Protein Characterization and Advanced Analysis
* L9 f$ p, N6 {* ^/ Nof Proteomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
+ q2 f3 r" ^) g0 B5 z8 XAlicia Lundby and Jesper V. Olsen
1 D+ K2 g$ n, z3 H6 L! q11. Exploring New Proteome Space: Combining Lys-N Proteolytic Digestion  N7 o* a  h5 l) \) s9 b! F7 I
and Strong Cation Exchange (SCX) Separation in Peptide-Centric
- k6 t7 ~( H* Z" m5 B; P+ C  o* eMS-Driven Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
/ t3 V( D5 J" U/ S12. Quantitation of Newly Synthesized Proteins by Pulse Labeling
; B. R/ G6 B, s9 }with Azidohomoalanine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
. Y, n* j/ {: r5 A( jGertjan Kramer, Piotr T. Kasper, Luitzen de Jong, and Chris G. de Koster
4 Z4 z6 o# ~$ @# t13. Analytical Strategies in Mass Spectrometry-Based Phosphoproteomics . . . . . . . 183
: B0 u: m) V8 w+ J) U' f. DHeidi Rosenqvist, Juanying Ye, and Ole N. Jensen
2 _* ~, R6 `2 c14. A Protocol on the Use of Titanium Dioxide Chromatography9 q: }: ~! _& {
for Phosphoproteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215
# Y$ ^, @4 u: R3 F6 o( zMartijn W.H. Pinkse, Simone Lemeer, and Albert J.R. Heck1 |* E2 N  j5 H' k
15. Positional Proteomics at the N-Terminus as a Means of Proteome Simplification . 229# d* R6 `: m. w' j/ a
Gemma R. Davidson, Stuart D. Armstrong, and Robert J. Beynon
: J: T1 Y3 f! F- {16. N-Terminomics: A High-Content Screen for Protease Substrates1 G, b7 p) O- R: g- D
and Their Cleavage Sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243
# L( P! G2 l6 B2 d% ]John C. Timmer and Guy S. Salvesen
! _4 ^7 }* R9 N17. Protease Specificity Profiling by Tandem Mass Spectrometry Using
. m  G- l* G+ C4 Q4 }# NProteome-Derived Peptide Libraries . . . . . . . . . . . . . . . . . . . . . . . . 257
; ?; S  \" v% f8 j9 M  j: C' d+ _Oliver Schilling, Ulrich auf dem Keller, and Christopher M. Overall
- W: b( a8 G' }8 K5 u18. Identification of Proteolytic Products and Natural Protein N-Termini+ s  L$ @' }' K
by Terminal Amine Isotopic Labeling of Substrates (TAILS) . . . . . . . . . . . . 2736 m1 M  R+ V$ I7 E0 [
Alain Doucet, Oded Kleifeld, Jayachandran N. Kizhakkedathu,6 X; D8 q. b0 [3 @( g- Z
and Christopher M. Overall0 |6 X- A4 e9 A: b+ ^& R' F! M
19. Lectins as Tools to Select for Glycosylated Proteins . . . . . . . . . . . . . . . . 289
  l, F+ K& }$ UEls J.M. Van Damme
6 S( P6 i# @1 k: ]7 J# |20. Strong Cation Exchange Chromatography for Analysis of Sialylated Glycopeptides 2993 A# X9 W. e, U& o6 |: t  i9 ^
Katharina Lohrig, Albert Sickmann, and Urs Lewandrowski' {: E, R7 O( s: Z- n, Y2 A& D
21. Titanium Dioxide Enrichment of Sialic Acid-Containing Glycopeptides . . . . . . 309
& G' L9 N& |) v0 I6 lGiuseppe Palmisano, Sara E. Lendal, and Martin R. Larsen5 X  o# U& b' r- Y6 k$ m" S+ I& U2 W
22. Chemical De-O-glycosylation of Glycoproteins for Applications3 \/ `3 k6 s/ u- |) L- A/ d! H) m
in LC-Based Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323
2 b8 Z# M0 d; C$ P. e2 mFranz-Georg Hanisch% H1 [$ O- v9 Q
23. Ubiquitination and Degradation of Proteins . . . . . . . . . . . . . . . . . . . . 335
6 L# R. X& k1 P2 }. N% L3 @Yelena Kravtsova-Ivantsiv and Aaron Ciechanover
. e7 x- Q5 D" D) E3 [& U24. Bioinformatics Challenges in Mass Spectrometry-Driven Proteomics . . . . . . . 3598 S" ]% u. D% {: v6 g
Lennart Martens
, v% R: E$ Y1 \& b. D25. A Case Study on the Comparison of Different Software Tools: w* d2 W+ x8 B9 N4 h( d8 [/ |
for Automated Quantification of Peptides . . . . . . . . . . . . . . . . . . . . . 373* _- c" v; y( V
Niklaas Colaert, Joël Vandekerckhove, Lennart Martens,* z' [6 H' m6 Y8 m
and Kris Gevaert
+ u3 |# R, e& v* L2 T, `, l- kSubject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399
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