4th Multidimensional Chromatography Workshop Toronto (January, 2013) Herman C. Lam, Ph.D. Calibration & Validation Group
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1 4th Multidimensional Chromatography Workshop Toronto (January, 2013) Herman C. Lam, Ph.D. Calibration & Validation Group
2 MDLC for Shotgun Proteomics Introduction General concepts Advantages Challenges in implementation Applications Shotgun proteomics 2
3 Multidimensional chromatography TLC LC Anal. Chem. 2008, 80, Fractions 3
4 Peak capacity Peak capacity P is the number of peaks that would fit into a separation space Separation performance and utilization of separation space Isocratic Gradient tf tf t1 tr t1 Estimation: P = (t f t 1 )/ W t f = time for the final peak, t 1 = time for the void peak W average peak width W4 N = 16 ( tr / W4 ) 2 4
5 Peak capacity For a multidimensional chromatographic system P = P1 x P2 X P3. P1 = peak capacity of the first dimension P2 = peak capacity of the second dimension P3 = peak capacity of the third dimension 3 rd D, P3 1 st D, P1 Assumptions: The separation dimensions are orthogonal and no peak broadening 2 nd D, P2 5
6 Orthogonality Correlation between the mode of separation High orthogonality: low correlation between the modes of separation (eg. SCX and reversed phased) Geometric orthogonality concept 2D 2D 2D 1D 1D 1D (A) Non orthogonal system, 10% area coverage represents 0% orthogonality. (B) Hypothetical orthogonal system, full area coverage. (C) Random, ideally orthogonal, system, area coverage is 63% representing the 100% orthogonality. M. Gilar, Anal. Chem., 2005, 77 (19), pp
7 LC Column Orthogonality and Solvent Compatibility Orthogonality Solvent compatibility 7
8 Challenges for implementation of MDLC Off line Very tedious Sample lose On line Different separation mechanisms at work Optimization of D1 and D2 Solvent compatibility Multiple pumps and complex switch valve systems Long total run time: For 2D separation (T d1 + nt d2 ) T Run time n= number of fractions from D1) Volume of data and data analysis 8
9 Proteomics Proteomics deals with the large scale determination of gene and cellular functions directly at the protein level. Proteomics includes not only the identification and quantification of proteins, but also the determination of their localization, modifications, interactions, activities, and their functions. Bottom up Top down 9
10 Trypsin: Cleaves at lysine and arginine, unless either is followed by proline in C terminal direction Enzymatic Digestion LC Separation Cells Complex Peptide Mixture MS/MS Peptide sequences: SPAFDSIMAETLK AFDSLPDDIHE GGILAQSPFLIIK IIGHFYDDWCPL Database Search Proteins 10
11 Challenges of MS proteomics The complexity of biological samples (great dynamic range, huge numbers of proteins) in human cells, and at least in human plasma Dynamic range of a LC MS is about Ion suppression when peptides co elution Simple mixture Complex mixture Signal is suppressed 1.Not being picked for MS/MS 2.Poor MS/MS spectrum The limited scanning speed of MS a bh d e f g c 11
12 Advantages for MDLC Increase in peak capacity to reduce sample complexity Enable the analysis of very complex biological samples Eliminate interferences Can be automated for 0n line applications 12
13 SCX RP 2D combination High orthogonality and relatively easy to implement MudPIT (Multi Dimensional Protein Identification Technology) Cation exchange (elution with salt solution) Reverse phase (elution with acetonitrile) Low resolution in the SCX separation Peptides carryover to subsequent fractions ESI/MS MS Lau, E.; Lam, M. P. Y.; Siu, S. O.; Lo, C.; Chu, I. K., Mol. BioSyst. 2011, 7,
14 High ph RP Low ph RP System Reversed phase separation is based on hydrophobicity Orthogonality is related to differences in retention of peptides in RP under different ph Different charges of amino acid side chain at different ph RP RP provides comparable performance to SCX RP with a higher peak capacity in the first dimension Salt free eluents minimized risk of ion suppression 14
15 High ph RP Low ph RP System Step 1: Partial filling of the loop with fraction eluted from the 1 st Dimension high ph RP column Step 2: Transfer to 2 nd Dimension low ph RP column Step 3: Elution from 2 nd Dimension low ph RP column Step 4: Refill the loop with low ph mobile phase IK Chu: PROTEOMICS: Volume 11, Issue 11, pages ,
16 High ph RP Low ph RP System Analysis 0f Mouse embryonic fibroblasts and Zebra fish embryo lysates Mouse embryonic fibroblasts Zebra fish embryo Hydrophobicity 16
17 HILIC RP combination Challenges: Solvent compatibility and peptide solubility Peptides trapping by a RP columns Transfer to HILIC via a mixing loop RP elution IK Chu: J. Sep. Sci., 2012, 35, p 1755 HILIC elution and trapping by a SCX column 17
18 HILIC RP combination Rat pheochromocytoma lysate 18
19 3DLC High ph RP SCX Low ph RP Evolved from using SCX as trapping column to separation column 1 st Dimension 2 nd Dimension 3 rd Dimension 19
20 Analysis of STO mouse cell digest 3D RP SCX RP (8 high ph RP fractions x 3 SCX fractions, 24 fractions in total) In comparison, 2D RP SCX (as trap column) RP (12 high ph fractions) No. of unique peptide (15523 vs ) 70.0% increase No. of proteins (2985 vs. 3613) 17.4 % increase Protein sequence coverage 2D 13.8% (5.2 peptides/protein) 3D 18.9% (7.3 peptides/protein) 20
21 Correlation of hydrophobicity across fractions 2D RP-SCX-RP 3D RP-SCX-RP Charge separation in SCX fractionation Peptide carryover Sufficient for tryptic peptides (+2,+3 and +4)
22 Capillary-/nano-flow 3D RP-SCX-RP MS/MS 1 st Dimension Capillary-flow 2 nd Dimension Capillary-flow 3 rd Dimension Nano-flow Peptide identification Protein identification ~ 50% protein of yeast proteome 22
23 Outlook and Summary MDLC has a key role in the analysis of highly complex samples in proteomics applications Suitable of Isobaric Tags for Relative and Absolute Quantitation (itraq) base quantitative proteomics applications Future areas of MDLC research in Dr. I.K. Chu Group Other column combinations Runtime reduction 4DLC separation Applications on system biology 23
24 Acknowledgements Dr. Ivan Chu and members of his research group at the University of Hong Kong Dr. Ricky Ng Dr. Ricky Kong Dr. S. O. Siu Dr. Maggie Lam Yun Zhao Edward Lau Henry Law Quan Quan 24
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