1. Introduction to 2D LC- MS/MS (Yuanming Luo) Institute of Microbiology Chinese Academy of Sciences

2. Fully integrated 2D-LC/ion trap MS

3. Hardware Improvement ---- New Orthogonal Ion Source Square Quadrupole New Inter-Octapole Lens New Endcap Electrodes Entrance Lens Attomole Sensitivity !!!

4. 1D-strong cation exchange column (Biobasic SCX)

5. Pressure cell

7. Xcalibur- control the instrument

8. Bioworks 3.1-database search software package containing SEQUEST

9. Application of 2D LC-MS/MS  Molecular weight determination  2D gel spots (especially the spots that can’t be identified by PMF analysis)  Protein complex (after primary factionation)  Proteome separation and identification  Multi-dimensional liquid chromatography MS-based differential proteomics  Quantitative proteomics (including ICAT or stable isotope labeling-based differential proteome analysis)  Analysis of posttranslational modification (data dependent)

10. Molecular weight determination of myoglobin by BIOMASS Calculation

11. Mr:16951.38+ /-0.33

12. High throughput gel spot analysis

13. Tandem RP Columns

14. Automated Protein Identification of 2-D gel spots ? Sensitivity and Throughput !!! SEQUEST Cross-Correlation Comparison Protein identified Digest

16. High throughput gel spot analysis 1. Protein mixture is separated by 2D gel electrophoresis 2. Excise target gel spot 3. Perform in-gel digestion with trypsin. 4. Extract peptides from gel spot. 5. Run peptide mixture with ProteomeX in 1D High Throughput mode. 6. Data search by TurboSEQUEST software

17. ProteomeX Analysis of 2D Gel Spots Using ProteomeX High Throughput Method 65.73 70.49 21.95 45.20 82.59 28.64 19.5341.22 13.77 83.90 100.31 22.68 51.85 79.67 72.35 70.5823.16 35.66 40.14 82.29 22.05 17.20 3.68 95.10 61.76 21.83 51.89 65.7770.2936.7743.07 34.1680.86 82.44 20.55100.61 8.82 0.48 63.93 23.06 29.58 39.32 51.72 79.87 65.88 35.1242.52 59.2017.4482.27 15.18 97.304.34 61.60 21.90 51.85 70.37 48.81 19.6237.34 72.6481.2627.77 12.701.26 98.74 85.70 22.74 51.83 79.86 63.79 70.37 54.56 48.00 29.5681.19 44.47 21.28 11.13 84.87 92.89 8.54 NL: 2.39E7 Base Peak F: + c Full ms [ 300.00-2000.00] MS GelSpot_tPA1_C1 NL: 9.02E6 Base Peak F: + c Full ms [ 300.00-2000.00] MS gelspot_tpa2_c2 NL: 1.16E7 Base Peak F: + c Full ms [ 300.00-2000.00] MS gelspot_tpa3_c1 NL: 1.41E7 Base Peak F: + c Full ms [ 300.00-2000.00] MS gelspot_tpa4_c2 NL: 2.11E7 Base Peak F: + c Full ms [ 300.00-2000.00] MS gelspot_tpa5_c1 NL: 1.15E7 Base Peak F: + c Full ms [ 300.00-2000.00] MS gelspot_tpa6_c2 NL: 8.00E6 Base Peak F: + c Full ms [ 300.00-2000.00] MS gelspot_tpa7_c1 Spot 1 2 3 4 5 6 7 Found t-PA

18. Global Protein Identification

19. Protein mixtureProtein digests SCX column fractionation Reverse column separation Auto MS/MS detection Tandem MS spectra BioWorks data base search Results

20. Plumbing Diagrams for Proteome X. 1D-SCX column 2D-RP1 column 2D-RP2 column

21. Global Protein Identification 1. Extract proteins from cell lysates 2. Reduce proteins to peptide fragments by tryptic digestion. 3. Analyze peptide mixture by 2D LC-MS/MS with ProteomeX. 4. Peptide and proteins identified by TurboSEQUEST software.

22. Protease Digestion of Proteins

23. 1D LC-MS/MS of proteins from A431 cell lysates RT:0.00 - 600.00 050100150200250300350400450500550600 Time (min) 0 50 100 0 50 100 0 50 100 Relative Abundance 0 50 100 0 50 100 33.95 431.84 35.12 1163.80 26.66 652.24 42.92 1138.32 76.43 667.61 68.71 1160.53 50.66 486.92 117.86 563.10 138.63 703.32 148.78 371.00 14.27 344.05 84.72 1154.55 200.37 563.16 17.79 388.10 118.32 431.94 258.97 776.40 140.05 1839.77 228.84 619.48 269.22 444.83 520.91 1912.57 432.24 675.17 8.40 439.73362.07 675.25 341.64 675.16 382.40 675.26 524.05 1511.36 465.75 488.12 294.93 576.29 171.60 1154.56 123.05 926.00 268.84 1285.77 226.50 794.78 12.29 390.90 113.04 897.74 575.63 444.75 NL: 2.28E9 Base Peak MS A431_30min G_1029 NL: 2.65E9 Base Peak MS a431_60min g_1029 NL: 1.28E9 Base Peak MS a431_120mi ng_1029 NL: 1.49E9 Base Peak MS a431_240mi ng_1029 NL: 4.60E8 Base Peak MS a431_1213_ 8hrg 30 min gradient 60 min 120 min 240 min 480 min

24. 2D LC-MS/MS of proteins from A431 cell lysates

25. Analysis of proteins from A431 cell lysates 56240min 105480min 44120min 2260min 1630min # of Proteins Identified Gradient 1D 49120 hr. 33710 hr. 1445 hr. # of Proteins Identified Total Run Time 2D

26. Yeast Protein separation 20 mM Ammonium chloride, 40 mM Ammonium chloride, 70 mM Ammonium chloride, 100 mM Ammonium chloride,

27. Yeast Protein Separation 140 mM Ammonium chloride, 180 mM Ammonium chloride, 220 mM Ammonium chloride,

28. Yeast proteins

29. Protein # 1708

30. 2D LC-MS/MS of Yeast proteins Time: 15 hours Gradient: 5 – 65% Acetonitrile in 2 hrs in each step Proteins searched by Bioworks 3.1 Proteins identified: 1708 Throughput: 113.8 proteins/hr

31. Viewing Results

32. Synclein alpha TIC

34. Filters for SEQUEST Results  Xcorr ： +1>1.5, +2>2.0, +3>2.5  ∆CN: >0.1  When three or fewer peptides for an individual protein passed the criteria (1) the spectrum quality (S/N, match rate) (2) some continuity must be present among the b or y fragments (3) if proline is predicted to be present, then the corresponding y fragment should give an intense peak. (4) unidentified intense peaks should be verified as being either doubly charged.

35. Filters for SEQUEST Results

36. On-Line Phosphopeptide Enrichment (IMAC capture)

37. Flow Path of an Automated 2D (IMAC + RP)-MS/MS System for the Analysis of Phosphopeptides

38. Procedure Used for Automated 2D LC(IMAC+RP)- MS/MS Analysis of Phosphopeptides Step 1: Load IMAC column Step 2: Load peptides on IMAC column. Flow-through peptides captured by RP2 column. Step 3: Wash IMAC column. The bound peptides are then eluted by phosphate buffer on to RP1, while the flow-through peptides trapped on RP2 are being analyzed by LC/MS. Step 4: The bound phosphopeptides on RP1 are analyzed by LC/MS/MS.

39. Capture of FQ*SEEQQQTEDELQDK Phosphopeptide of -Casein Digest in the 2D LC(IMAC+RP)-MS/MS System Non-phosphorylated peptides flow through IMAC column and captured by and eluted from RP2 Phosphorylated peptide (m/z=1031.7, FQ*SEEQQQTEDELQDK) captured by IMAC column, bound to RP1, and eluted. NL: 1.34E9 NL: 1.80E8 position for m/z=1031.7 on C2 column RP2 column RP1 column

40. Neutral Loss Scanning Confirmed the Major Ion at m/z=1031.6 as a P-peptide Neutral loss fragment (-49) M+2H + -49 MS/MS of 1031.6 Phosphorylated peptide (m/z=1031.7, FQ*SEEQQQTEDELQDK)

41. Bioworks 3.1 Search Identified the P-peptide with m/z=1031.6 as FQ*SEEQQQTEDELQDK 1+ 2+ (M+2H)-49

42. Proteins - Differential Expression (EGF treated and untreated cells) ---- Alternative method for differential analysis of protein expression compared to 2DE strategy

43. Protein differential expression 1. Divide A431 cell sample in two: a) Half stimulated by EGF b) Half control 2. Lyse cells 3. Extract proteins from lysates 4. Digest with trypsin 5. Run 2D LC-MS/MS of digests with ProteomeX 6. Proteins identified by TurboSEQUEST software 7. Compare “stimulated” vs. “control”

44. Automated 2D LC-MS/MS Analysis of Human A431 Cell Proteins 120 mM 10 mM 20 mM 40 mM 60 mM NH 4 Cl 0 mM 80 mM 160 mM

45. Automated 2D-LC-LC/MS-MS Analysis of Human A431 Cell Proteins (continued) 200mM 300mM 500mM 900mM Total Proteins Identified= 709, using Bioworks 3.1 with TurboSequest (Xcorr = 1.5, 2.0, and 3 for charge states +1, +2, and +3, respectively )

46. Proteins Differentially Expressed in Control and EGF- Stimulated A431 Cells

47. Proteins Differentially Expressed in Control and EGF-Stimulated A431 Cells (continued) *Only those proteins with two or more peptides identified were compared

48. Proteins Identified in Both Control and EGF- Treated A431 Cells

49. Proteins Common to Control and EGF-treated A431 Cells (continued)

51. Differential Protein quantitation -quantitative proteomics

52. Stable isotope labeling (SIL) for quanlitative proteomics  Metabolic labeling ( 13 C, 15 N)  Post-biosynthetic labeling (ICAT reagent)  Post-digest isotope Labeling of tryptic peptides( 18 O)

53. Metabolic labeling with [ 13 C 6 ]Arg in the elucidation of EGF signaling  Cells were grown in medium containing either normal or [ 13 C 6 ] arginine.  8 h of serum starvation, the labeled cells were stimulated with 150ng/ml EGF for 10 min, whereas the unlabeled cells were left untreated.  Cells were lysed and combined in a 1:1 ratio followed by incubating at 4°C with Grb2 fusion protein bound to GSH-sepharose beads for 4h.  Wash with lysis buffer, boiled in sample buffer, and resolved on a 4-12% gel.  Bands of interest were excised and subjected to in gel digestion.  Mass spectrometric analysis

54. Strategy to study activated EGFR complex SH2 domain of Gb2 binds tyrosine-phosphorylated proteins including EGFR, Shc etc.,

55. Quantification of protein ratios from peptide doublets. Top panels show mass spectra of peptides of different identified proteins, bottom panels show mass spectra of peptides from EGF-stimulated cells upon detection of autophosphorylation

56. Metabolic labeling  Advantages: (1) all sample-to-sample variability induced by subsequent biochemical experiments can be eliminated. (2) metabolism-related dynamic labeling involved in a specific physiological process.

57.  Drawbacks: (1)only works in cell culture systems that tolerate isotope-substituted media (which is actually often not the case), which may not be compatible with a particular biological investigation. (2)Total isotope substitution is required for reliable for MS-based quantification, which renders the approach rather expensive. (3)Difficulty in establishing an enrichment method

58. Differential Quantitation with isotope-coded affinity tags (ICAT) 1.Divide the previous sample (hGH in plasma) into two identical pools. 2.Reduce and alkylate (D0 ICAT for one plasma pool and D8 ICAT for the other), separately. Mix the two pools and digest the whole mixture with trypsin. 3.Sample clean-up a)ion exchange to remove excess ICAT reagent b)avidin affinity to capture the ICAT-labeled peptides 4.Collect the ICAT-peptide fractions and run LC-MS/MS. 5.Data analysis by Bioworks 3.1 a)TurboSEQUEST for protein identification b)XPRESS for relative quantitation ProteomeX (2D) Collect the flow through Frxn ProteomeX (2D) ProteomeX (1D)

59. The structure of ICAT reagent

60. Data Dependent Mass Tag Setting for ICAT 1+ 2+ 3+

61. TurboSEQUEST Search Parameters Turbosequest parameters are set as usual except the amino acid modification and differential mass need to be set as in above

62. Bioworks 3.1 (SEQUEST and XPRESS) Search Results 200mM NH4Cl

63. Differential Quantitation by Bioworks (XPRESS) Software NYGLLYCFR (T16 peptide of human growth hormone) * After finishing the TurboSEQUEST search, click the XPRESS function to locate the correct cysteine- containing peptide sequence (identified from its MS/MS spectrum) with the ratio of D0 and D8 ion intensities (integrated from its parent ion spectrum) as shown in above.

64. 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100 Relative Abundance 35.29 35.25 35.20 35.33 35.16 35.33 35.29 35.20 NL: 9.68E5 Base Peak m/z= 798.6-799.6 MS NL: 1.09E6 Base Peak m/z= 794.4-795.4 MS M/Z = 799.1 Signal = 0.986 M/Z = 794.9 Signal =1.09 D0/D8 = 1.1 Zoom In MS spectra (+2) Charge D8 (+2) Charge D0 Using the highest MS intensity

65.  Advantage: (1)Largely reduce the complexity of peptide mixture; (2)Easy to enrich.  Drawbacks: (1) 14% protein sequences do not contain cysteine-containing tryptic peptides (800-2500Da),19% contains just a single such peptide (alternatively, cleavable ICAT reagents). (2) requirement of protein over 100  g.

66. Post-digestion isotope labeling ( 18 O)  Artifacts (i.e. side reactions) inherent to chemical labeling can be avoided.  All peptides can be used for identification and quantification  Available for gel-separated proteins

67.  Samples of interest are first digested with trypsin.  Aliquots are subsequently incubated with either 16 O water or 18 O water in the presence of trypsin. Labeling efficiencies of individual peptides of the H 2 18 O-treated sample are determined by MALDI- TOFMS of a small portion of the sample. Mixtures of 16 O- and 18 O-labeled samples are then applied on the MALDI plate, and relative abundances are derived from relative isotopomer abundances.

68. General scheme of post-digest 18 O labeling procedure

69. Time course of trypsin-catalyzed post-digest labeling of 1 pmol BSA tryptic digest. The exchange rate of C-terminal oxygen atoms is dependent on the peptide sequence. Fast exchanging peptides show complete labeling after <10 min (a). However, for some peptides close to quantitative labeling could only be achieved after incubation for 2 h (c).

70. Practical considerations for stable isotope labeling in quantitative proteomics  Predictable mass difference between labeled and unlabeled samples  Easy to enrich

71. An example of Data dependent MS/MS mode- reject high abundant proteins(GDH-2)

72. Glutamate dehydrogenase 2 1193.29 1759.92

73. Data dependent setup for rejecting high abundant GDH-2 Just ion of interest

74. Post-Translational Modifications

75. Modifications

76. Modifications (continued)

78. Phosphorylation

79. Protein identification: Phosphorylation

80. Data Dependent (with Dynamic Exclusion) MS/MS spectrum of m/z 980-982 % Relative Abundance 40060080010001200140016001800 0 10 20 30 40 50 60 70 80 90 100 931.8 1311.5 922.7 1099.5 764.6 551.1 452.5 1591.5 1410.6 1689.7 1083.1366.4 665.3 1786.8 Y ’’ 12 +1 (MH 2 - H 3 PO 4 ) 2+ Y ’’ 10 +1 Arg-Leu-Ser-Leu-Val-Pro-Asp-Ser-Glu-Gln-Gly-Glu-Ala-Ile-Leu-Pro-Arg Y ” 12 +1 Y ” 10 +1 Serine Not Phosphorylated Serine Phosphorylated

81. Glycosylations

82. Glycosylation

85. Identifying Glycosylation – MS full scan RT:0.00 - 140.00 0102030405060708090100110120130 Time (min) 0 10 20 30 40 50 60 70 80 90 100 Relative Abundance 46.78 31.08 34.55 29.80 44.66 26.55 5.32 56.23 6.06 97.61 49.19 96.92 121.72 113.398.59 57.42 98.2595.93 21.91 110.9821.55 88.2461.02 117.35 64.91 13.23 86.75 70.50 75.92 122.46 138.88 NL: 2.79E10 TIC MS #583RT:15.57AV:1NL:7.23E8 T:+ c Full ms [ 200.00-2000.00] 200400600800100012001400160018002000 m/z 0 5 10 15 20 Relative Abundance 527.5 217.0 575.8 1064.0 234.1 445.0 634.8 286.8 1095.7 762.3 1060.7 807.91267.6 1595.2 1780.21514.8 1987.9 Glycopeptide region MS from glycopeptide ion MS scan +3 +2 As n Fu N (select to do MS/MS) Glycopeptide region 1 2 3 4 Other region perform only MS and MS/MS

86. Identifying Glycosylation – MS/MS

87. Identifying Glycosylation – MS 3

88. Identifying Glycosylation – MS 4

89. Summary of one glycopeptide fragmentation pathway (a biantennary glycopeptide)

90. De Novo Peptide Sequencing

91. Why De Novo Peptide Sequencing ? Determination and/or confirmation of peptide sequences derived from proteins that are:  not in the databases (including DNA sequence)  with amino acid modifications

92.  De novo sequencing software (PARSER II)  Ref: Zhang ZQ, McElvain JS. De Novo peptide sequencing by two-dimensional fragment correlation mass spectrometry. Anal Chem, 2000, 72 (11): 2337-2350

93. MS, MS 2 and MS 3 spectra collected with peak parking 16 18202224 Time (min) 0 20 40 60 80 100 Base Peak 400 600 80010001200 m/z 496.1 990.6 Full Scan MS 2004006008001000 m/z 0 20 40 60 80 100 730.4 389.2 261.1 233.1 616.4 732.4 502.4 Full Scan MS2 * * * * * 100200300400 m/z 120.2 86.1 121.2 4008001200 m/z 713.4 714.5 389.2 502.3 Full Scan MS3 @233.1 Full Scan MS3 @730.4 100200300400500 m/z 0 233.1 234.1 200400600 m/z 261.2 226.1 243.0 129.1 372.2 354.1 2004006008001000 m/z 581.2 599.3 Full Scan MS3 @261.1 Full Scan MS3 @389.2 Full Scan MS3 @616.4

94. Determination of Peptide Sequence by MS 3 De Novo Sequencing Software --- Biowork 3.1 Peptide = FINNIGANK

95. Sequencing Tryptic Peptide (m/z 585.1) by MS 3 De Novo Sequencing Software Peptide = TGPNLHGLFGR

96. Thank You!