Increasing MS Sensitivity for Proteomics. ifunnel Technology for the QQQ and Q-TOF

Size: px
Start display at page:

Download "Increasing MS Sensitivity for Proteomics. ifunnel Technology for the QQQ and Q-TOF"

Transcription

1 Increasing MS Sensitivity for Proteomics ifunnel Technology for the QQQ and Q-TOF

2 Improving Sensitivity: ifunnel Technology in the Agilent 6490 QQQ and 6550 Q-TOF More efficient ionization Thermal confinement of ESI ion plume Efficient desolvation to create gas phase ions Increased ion sampling 6 capillary inlets Samples 12x more ion rich gas from the source Greater ion transfer Removes the gas but captures the ions Helps to remove source generated noise Heat Sink with Forced Air Cooling Nebulizer Heated Sheath Gas Thermal Gradient Focusing Region MS Inlet High Pressure Funnel Low Pressure Funnel 2

3 Impact of Ion Funnel on QQQ Sensitivity 1 fmol on-column LVNEVTEFAK Observed a 5-10x increase in sensitivity Linear dynamic range (standard flow): 6460: 200 fmol to 25 pmol on-column 6490: 20 amol to 25 pmol on-column 6460 QQQ 6490 QQQ with ifunnel technology 3

4 Robust, Reproducible Quantitation in Digested Plasma Using the UHPLC/QQQ Protein Adiponectin: IFYNQQNHYDGSTGK Antithrombin-III : DDLYVSDAFHK Apolipoprotein A-II precursor: SPELQAEAK Apolipoprotein C-III: GWVTDGFSSLK Ceruloplasmin : EYTDASFTNR Heparin cofactor II: TLEAQLTPR Histidine-rich glycoprotein: DGYLFQLLR Kininogen-1: TVGSDTFYSFK L-selectin: AEIEYLEK Plasminogen: LFLEPTR Vitamin D-binding protein: THLPEVFLSK von Willebrand Factor: ILAGPAGDSNVVK Response %RSD Ret. Time %RSD Plasminogen LFLEPTR 7.9% RSD, n=4 12.3% RSD, n=4 2.2% RSD n= % RSD, n=4 The samples were provided by Derek Smith and Christoph H. Borchers from the UVic-Genome BC Proteomics Centre 4

5 HPLC-Chip/Q-TOF Increases Sensitivity for Protein Identification 10 amol BSA Digest On-column MS MS/MS From 4-8 unique peptides (n=3) 5

6 Protein Discovery with the 6550 Q-TOF High Sensitivity Protein Identification

7 Protein Identification Scaffold Spectrum Mill MPP and Pathway Analysis Shotgun: find all proteins present Differentially expressed (label and label free) Targeted identification Identify Proteins 7

8 Spectrum Mill B.04.00: New Release 8

9 Spectrum Mill B.04 Just Released: New Features Automated workflows with saved parameter files Autovalidation with FDR and new Auto Thresholding strategies Variable Modification Localization (VML) probability scoring for PTMs MRM Selector for creating MRM methods from protein id results Peptide Selector for exporting targeted QQQ MRM, QTOF inclusion lists, and accurate mass csv databases from a list of protein accession numbers Integration with MPP workflows via AMRT export and ID Browser Integrated Biology with MPP Pathways Support for Scaffold, PepXML export (Skyline, TPP) 9

10 Spectrum Mill B.04: Post-translational Modification (PTM) Site Localization VML score = Difference in Score of same identified sequences with different variable modification localizations 10

11 New Proteomics Software Suite Including Scaffold Scaffold Proteomics Software Scaffold Software from Proteomics Software of Portland, Oregon Allows users to combine results from multiple search engines (Spectrum Mill, Mascot, SEQUEST, etc.) for increased confidence in protein identifications Scaffold contains tools to produce Venn diagrams of protein searches and classify protein identifications by GO categories: 11

12 Spectrum Mill MPP Data Exchange: A Unique Agilent Advantage 12

13 Multi-Omics Analysis in MPP Protein Data Overlay Metabolite Data Overlay Filtered data projected on curated pathways Export a list of proteins based on pathway analysis 13

14 Protein Discovery to Targeted Protein Analysis Spectrum Mill Protein data base search Protein-protein comparison of all results Export of protein abundance in MPP format Mass Profiler Pro Statistical analysis and visualization of differential proteins Pathway analysis of differential features Export of protein accession numbers Spectrum Mill Use discovery data to develop MRM or inclusion list from protein accession numbers In silico prediction of peptides based on protein accession numbers Target Analysis (Q-TOF or QQQ) Inclusion list (with RT) or targeted mode on Q-TOF MRM or DMRM method on QQQ Export Quant results to MPP for analysis 14 LBMSDG

15 Genomics/Metabolomics Discovery to Target Proteins Analysis Mass Profiler Pro or GeneSpring Process genomics/metabolomics data to find significant differences Map differential features to pathways Export protein accession numbers Spectrum Mill Peptide Selector predicts possible peptides and precursors for target proteins Export as inclusion list for data directed LC/MS/MS analysis Q-TOF Acquire data on QTOF using inclusion list and datadirected mode Spectrum Mill Search data in Spectrum Mill and find one-hit and missing Loop until satisfied with protein coverage and peptide surrogates 15 LBMSDG

16 Label-free Protein Discovery Results for HeLa Cell Lysates Treated HeLa cell lysates (Millipore) trypsinized then analyzed by LC/MS/MS (n=4) Protein database search in Spectrum Mill Protein-protein comparison in Spectrum Mill groups proteins across the entire set Color coding = abundance (based on EIC of peptides assigned to the protein) Export results to MPP Injection Protein Group Control HS-Ars IFN TNF Treatments: HS-Ars = heat-shock + arsenite IFN = interferon TNF = tumor necrosis factor 16 LBMSDG

17 Statistical Analysis and Visualization of Protein Identification Results One-way ANOVA followed by PCA of differential proteins 17 LBMSDG

18 Statistical Analysis and Visualization of Protein Identification Results 18 LBMSDG

19 Pathway Analysis of the Differential Proteins Between HeLa Cell Lysates: Apoptotic Pathway 19 LBMSDG

20 Pathway Directed Experiment: Target Protein List Is Exported To Spectrum Mill Create list of target peptides for proteomics study Measure changes in protein expression level Detect post-translational modifications Copy protein accession numbers from Pathway Architect Generate peptide lists for: QQQ MRM Q-TOF target list 20 LBMSDG

21 Development of MRM-based Methods for Non- Detected Target Proteins 21 LBMSDG

22 Improvements for Increasing Protein Identification Increased identifications Data dependent acquisition (DDA) Chromatography Q-TOF mass spectrometer Recognize peptide isotope pattern Better phase (Polaris) Increase sensitivity Select pure precursors Improved chip manufacturing Increase speed to acquire more MS/MS Optimize MS/MS accumulation time 22

23 DDA: On-the fly Determination of Precursor Purity Intended precursor must be at least 30% of precursor signal in the isolation window Meets 30% criteria mixed MS/MS but can ID 30% precursor purity threshold Isolation window Dominant precursor will give good MS/MS Precursor below purity TH. MS/MS will not be done 23

24 Acc. Time (ms) DDA: On-the fly Optimization of MS/MS Acquisition Time Based on Precursor Intensity Power ramp relationship Increased protein identified Increased # of MS/MS Faster cycle times MS precursor abundance 24

25 Improved Chromatography With Polaris C18, 3 µm Stationary Phase Improved Protein ID Zorbax 300SB-C18 Jupiter MagicAQ SB-AQ/Reprosil Extend C18/Reprosil MetaSil Polaris Best of tested phases Narrower peaks than existing HPLC-Chips Good performance with high sample load 25

26 Unique Peptides Identified Protein Identified Increase in Protein Identification With Increased Sensitivity Same number of identifications with 10x less sample! vs. 6550: Peptides vs. 6550: Proteins x less sample! x less sample! ng loaded ng loaded 26

27 Unique Peptides Identified Unique Proteins Identified Effect of Gradient Time on Protein Identification: E. coli Lysate Unique Peptides Proteins ng E. coli lysate 1% FDR Gradient Time Gradient Time 27

28 Targeted Proteomics with the 6490 QQQ High Sensitivity Peptide Quantitation

29 Protein Discovery and Targeted Proteomic Workflows Scaffold Spectrum Mill Pathway Architect Proteomics Experiment Mass Profiler Pro Literature and other sources Target Proteins Metlin PCDL Metabolomics Experiment Genomics Experiment Mass Profiler Pro Pathway Architect GeneSpring Page 29 29

30 Skyline Targeted Proteomics Environment Open Source software Multi-vendor software Funded with CPTAC project Rapidly evolved using feedback from top-labs Widely used and highly regarded 30

31 Human SRM Atlas 31

32 SISCAPA: Enrich Target Peptides and Decrease Sample Complexity 32

33 L/H (fwd) or H/L (rev) Area Ratio L/H (fwd) or H/L (rev) Area Ratio CA125 Her-2 OPN PCI AFP FLC stfr Tg1 Tg2 Increasing Throughput Using SISCAPA to Enrich Target Peptides and Reduce Sample Complexity 100 Mesothelin curves (log/log) Agilent 6490 (400ul/min) + Bravo 100 Meso AB 4000 Qtrap (300nl/min) + Kingfisher LPSBP 10 Bravo1-Forward-Meso Bravo1-Reverse-Meso 10 Meso:Xlink:Reverse Meso:Xlink:Forward 1 Endogenous level: 3fmol/10ul = 16ng/ml 1 Endogenous level: 3fmol/10ul = 16ng/ml fmol Spiked Varying Peptide Standard flow ion funnel QQQ-MS fmol Spiked Varying Peptide Reducing analysis time to 3 min 33 Lorne Conference

34 Magnetic Bead Implementation of SISCAPA Assay Technology Biomarker concentration Labeled standard Sample peptide MRM Chromatogram Agilent Bravo 34

35 42 Avg. Δ R.T ~ 2.4 s across 8 replicates over a 60-minute gradient