From Biomarker Discovery to Validation: Routine Nano-LC/QQQ for Quantitation of Peptides

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1 From Biomarker Discovery to Validation: Routine Nano-LC/QQQ for Quantitation of Peptides Jaume C. Morales LC/MS Product Specialist Agilent Technologies Page 1

2 Agilent Proteomics Biomarker Workflow SAMPLE1 Extraction SAMPLE2 Candidate Biomarker Identification DATA Depletion 6520 QTOF Candidates Fractionation Proteolytic Digest Extraction Validation 6410 QQQ Identification Page 2

3 Biomarker validation workflow Run samples on Q- TOF for protein ID in data-dependent MS/MS mode Step 1 Q-TOF Perform statistical analysis for identification of biomarker candidates Step 3 Spectrum Mill Search QTOF data using Spectrum Mill Use Spectrum Mill MRM Builder to create a list of MRM transitions with RT Integrate the MRM chromatograms Import quantitation results into MPP to perform statistical analysis Step 2 and 5 Mass Profiler Pro Run samples on QQQ in Dynamic MRM mode Step 4 QQQ Page 3 2/15/2011

4 Workflow for quantitative peptide analysis using MRM 1. Creation of a (D)MRM acquisiton method from discovery data MRM optimization QTOF acquisition SpectrumMill MRM Builder MRM acquisition Export MRM transitions and optional retention time information for optimization or direct (D)MRM acquisition analysis DMRM acquisition 1. Export transitions from SpectrumMill.wmv 2. Import SpectrumMill results into Optimizer for Peptides.wmv

5 Workflow for quantitative peptide analysis using MRM 2. In-silico prediction of MRM transitions SpectrumMill Peptide Selector MRM optimization 3. MRM acquisition Predict proteotypic peptides (BLAST search) and import optimized transitions into MRM method 1. Peptide selector import into MassHunter Qual.wmv 2. Import transitions from MassHunter Qual.wmv 3. Import transitions into MRM method.wmv

6 Workflow for quantitative peptide analysis using MRM 3. Generation of a (D)MRM acquisition method MRM optimization MRM acquisiton 3. DMRM acquisition Verify results from Optimizer for peptides and perform (D)MRM analysis 1. Optimizer for peptides data.wmv 2. Import transitions into MRM method.wmv 3. Update RT information for DMRM method.wmv

7 Prerequisites for successful profiling and quantitation of biomarkers Signal Response Sensitivity Linearity Reproducibility Separation Speed Peak Capacity Reproducibility Mass Spectrum Selectivity Acquisition Rate Page 7 2/15/2011

8 HPLC-Chip/QQQ LCMS Technology Nanospray chip configuration brings new era in high sensitivity quantitation NanoLC system for analytical chromatography HPLC Chip Cube system CapLC pump for sample loading on enrichment column QQQ LCMS Sensitivity: low -mid amol Dynamic range: Page 8

9 Triple Quadrupole Mass Spectrometer Extending Outstanding Performance 6400 Series Triple Quad NEW Functionality No Cross Talk collision cell commonality with QTOF Peptide Optimizer Dynamic MRM 4000 MRMs High Sensitivity 10attomols on peptides Page 9

10 HPLC-Chip/MS Interface: Fluid Connections to the HPLC-Chip Stator Autosampler Waste Nanopump Side View Rotor inner rotor Rotor outer rotor Stator Microvalve HPLC-Chip Page 10

11 Retention Time Reproducibility RT SD %RSD EIC EIC EIC EIC EIC EIC EIC Extracted ion chromatograms for 17 peaks from a EIC BSA tryptic digest (50 fmol on-column) EIC EIC EIC %RSD Interchip RT differences Applied Proteomics reference EIC EIC EIC EIC EIC EIC RT reproducibility evaluated using 69 repeat injections

12 Ion Intensity Reproducibility 1 5,5 Scatter plot of ions intensities Scatter plot of intensities: Run 1 vs, Run 10 5 log individual intensity 4,5 4 3,5 3 Replicate 1 Replicate 2 Replicate 3 Replicate 4 Replicate 5 2,5 N =234 2,5 3 3,5 4 4,5 5 5,5 log average intensity ions were monitored over 5 replicate runs ~ 94 % of all ions show less than 20% variation in intensity across all 5 replicates. HPLC-Chip/TOF 5000 glycopetides monitored over 10 replicate runs. HPLC-Chip/TOF 1 Data courtesy of Dr. Pierre Thibault University of 2 Data courtesy of Dr. H. Zhang, X.J. Li and Dr. R. Montréal Immunology and Cancer Research Institute Aebersold, Institut für Molekulare Systembiologie, Switzerland

13 Rapid Nanoflow LC/MS 3 Minute Analysis 21 MRM Transitions From 7 Peptides

14 MRM Optimizer for QQQ Programa que permite encontrar los méjores valores de Fragmentor y/o Energía de colisión para aquellas transiciones que nos interesan en base a su abundancia. Es necesario especificar la m/z de precursor y product ion. Peptide Optimizer for QQQ Caso particular del MRM optimizer. Las transiciones se especifican tan sólo detallando el péptido. El péptido escogido puede provenir de SM Peptide Selector o bien de MH Qual

15 Que es diferente en Peptide Optimizer? Secuencia de péptidos en lugar de fórmulas químicas Precursor generalmente +2 y/o +3 de estado de carga El espectro MS/MS muestra varios product ions Algunos product ions tienen m/z > precursor m/z Es predecible la fragmentación de los deseados iones b y y aunque algunos product ions pueden presentar también multicarga Típicamente se buscan 2-3 péptidos por proteína y 2-3 transiciones por péptido.

16 Desarrollo y Optimización de métodos SRM para Péptidos Selección de transiciones basada en Observaciones de MS/MS durante el descubrimiento ó predicciones de iones b y y. Predicción de exclusividad de la secuencia peptídica en la base de datos. Optimización de las transiciones El parámetro más importante en QQQ es la energía de colisión. Debe seleccionar las transiciones que ofrezcan una mayor relación S/N y menor interferencias en la matriz.

17 MRM Method Optimizer for Peptides Ejecutar Optimizer: Importar las secuencias de péptidos, luego ver las predicciones de fragmentos b/y y seleccionar iones para la optimización. Run 1 (MRM): Optimiza la CE en modo MRM utilizando la fórmula del Q-TOF como punto de partida, en un sólo análisis. Ventajas: Reduce considerablemente la cantidad de muestra utilizada. Puede optimizar en más de una carga para el mismo péptido. Pre-selección de iones b/y (incluyendo multicarga) El único límite está en el numero total de transiciones por inyección de optimización. El propio software nos da información basado en la anchura de los picos y Cycle Time. Conviene adquirir 10 puntos por pico.

18 Enter Sequences and Select b/y Ions For Optimization

19 Results of Peptide Optimization Peptide sequence Precursor Optimized product ions Abundance of each transition allows customer to choose best transitions for the final method 19

20 Dynamic MRM Comparison of MRM and Dynamic MRM Time Segment 1 Time Segment 2 Time Segment 3 Time Segment 4 Time (min) MRM Compounds (10/block) Cycle Time (sec) Dynamic MRM Max Coincident Cycle Time (sec) x shorter cycle times supports narrow chromatographic peaks, more analytes or longer dwell per analyte. Page 20

21 Dynamic MRM what happens? Increases Sensitivity Improves cycle time Provides better chromatographic definition 4 ions not 11 7 ions - not 11 Page 21

22 Dynamic MRM: Retention Time Based Scheduling of MRM for Optimal Sensitivity

23 Absolute Protein Quantification in the Context of Non-clinical Drug Safety Evaluation UCD Conway Institute University college Dublin And Agilent Technologies Vehicle Low Dose High Dose Day 2,4,15 Day 2,4,15 Day 2,4,15 Day -3/-4, 1/2, 3/4, 12/13 Histopathology Histopathology Transcriptomics Metabonomics Transcriptomics Transcriptomics Proteomics Clinical Biochemistry Proteomics Proteomics Metabonomics Clinical Biochemistry Collins B. C. et al. ASMS 2008 MPQ 477 Page 23

24 Experimental Design Catalase was selected based on previous 2D-DIGE data Rat liver lysate were prepared from rats treated with troglitazone or vehicle control Peptides and MRM transitions were selected using Peptide Selector in Spectrum Mill and 13C, 15N labeled peptides were synthesized 1 mg of soluble protein extract was reduced, alkylated, acetone precipitated and trypsin digested The liver digest were spiked with the isotope-labeled peptides and analyzed by Agilent 6410 QQQ system Page 24

25 Using Spectrum Mill Peptide Selector for Optimising MRM Transitions Chemically reactive residues (Cys = C, Met = M, Trp = W) Peptides adjacent to multiple cleavage site Chemically unstable residues (Asp-Gly = D-G; Asn-Gly = N-G; N-term Glu = E; N-term Asn = N) Eliminate LC-incompatible peptides Uniqueness Page 25

26 Spectrum Mill Peptide Selector Page 26

27 Peptide Selector Catalase Results Page 27

28 Catalase Peptide LAQ Peptide Selector Page 28

29 Catalase Peptide EAE Peptide Selector Page 29

30 External Calibration on Catalase Peptides Linearity : five order of magnitude 78aMol 78fMol 780 fmol External quantitation curve of catalase peptide L*AQEDPDYGLR from 78 amol to 7800 fmol RSD < 6% Page 30

31 Catalase Quantitation Results Page 31

32 Quantitation of protein phosphorylation using MRM Erk1 protein was quantified from depleted human serum. +2 PO4 +3 PO4 +4 PO4 Erk1 intact protein Page 32 Peptide MRM Lorne

33 Selection of MRM transitions b 14 TY: IADPEHDHTGFLTEYVATR y 16 t202: IADPEHDHTGFLTEYVATR y 16 y 16 P y 5 y 5 y204: IADPEHDHTGFLTEYVATR P P t202y204: IADPEHDHTGFLTEYVATR P y 5 y 5 TY t202 y204 t202y204 Precursor ion Product ions [M+3H] 3+ y 5 b [M+2H] 2+ y 5 y [M+2H] 2+ y y [M+2H] 2+ y H 3 PO 4 y 5 Page 33

34 Chromatographic Separation of the Four Peptide Standards allowed the selection of the same Q1 and Q3 transitions for two different peptides x MRM ( > ) mix500f-r001.d y204 t202y204 TY t Counts vs. Acquisition Time (min) Page 34

35 TY13-5 Levels, 5 Levels Used, 15 Points, 15 Points Used, 0 QCs x10 2 y = * x R^2 = fm fm fm Relative Responses Relative Responses R 2 = TY T432tY434y13-5 Levels, 5 Levels Used, 15 Points, 15 Points Used, 0 QCs x10 1 y = * x R^2 = fm 2.5fm 5fm Relative Responses Relative Responses R 2 = t202y Concentration (fmol/ul) Concentration (fmol/ul) Y434y13-5 Levels, 5 Levels Used, 15 Points, 15 Points Used, 0 QCs x10 2 y = * x R^2 = Relative Responses Relative Responses 0.5f m 2.5f m 5f m R 2 = y Concentration (fmol/ul) T432t13-5 Levels, 5 Levels Used, 15 Points, 15 Points Used, 0 QCs x10 1 y = * x R^2 = Relative Responses Relative Responses 0.5fm 2.5fm 5fm R 2 = t Concentration (fmol/ul) Page 35

36 Quantitation of the degree of phosphorylation at T202 and Y204 in active Erk1 protein peptide % Molar ratio RSD (n=9) TY 20% 0.13 t202 25% 0.15 y204 21% 0.12 t202y204 34% 0.08 In this batch of active Erk1 sample, 59% of T202 and 55% of Y204 were phosphorylated Page 36

37 From Discovery Mode to Validation Step Peroxidase in Human Plasma Page 37

38 Discovery phase to Validation : MRM Selector Biomarker validation workflow Run samples on Q- TOF for protein ID in data-dependent MS/MS mode. Step-1 Q-TOF Step-2 Spectrum Mill Search QTOF data using Spectrum Mill Use Spectrum Mill MRM Selector to create a list of MRM transitions with RT Import the MRM list into QQQ Acquisition software Run samples on QQQ in Dynamic MRM mode Step-3 QQQ Step Mass Prof Integrate the MRM chromatograms Import quantitation results into MPP to perform statistical analysis Page 38

39 Depleted Human Plasma Sample analysis Replicate LC/MS runs HPLC Chip / QTOF Spiked with 0,0.5 and 5fmol per 0.5ug plasma Data Dependent Protein IDs from Spectrum Mill Page 39

40 MRM Selector Generates MRM method from discovery QTOF data Page 40

41 Dynamic MRM Page 41

42 Dynamic MRM Overlaid 2000 MRM chromatograms acquired in a single run using Dynamic MRM Page 42

43 Sensitivity : Peroxidase in plasma matrix (per 0.5ug) M A B matrix 500amole 5fmol # MRM RT window (min) Cycle time (ms) Min. dwell (ms) Max. # concurrent MRM %RSD Area RSD RT (min) Reproducibility of MS response and RT Page 43

44 Mass Profiler Professional Statistical Processing of MRM Data Four peptides from peroxidase were highlighted in green. The mean of 443 MRM abundances is displayed (black) to show the peptides from plasma did not vary from sample to sample. B1 B2 B3 A1 A2 A3 M1 M2 All Samples Page 44

45 Principle Component Analysis Matrix and 2 different peroxidase levels Samples at different peroxidase concentrations were correctly grouped together. Page 45

46 Hierarchical Clustering comparing different peroxidase concns. A condition was generated with peroxidase concentration color-coded on the tree branches, along with the peptide features labeled on each row. The heat map is colored from blue to red, where blue is low abundance and red is high abundance. The full view of all the features is on the left. The zoom view is on the right. M1 M2 A1 A2 A3 B1 B2 B3 Page 46