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The ABRF Workflow Interest Network (WIN) is conducting a research study to identify factors contributing to poor reproducibility in MS laboratories and propose benchmarks for MS-based proteomics analysis. Participating labs will evaluate LC-MS/MS performance using peptide standards and a digested lysate.
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ABRF 2017 Annual Meeting Workflow Interest Network (WIN) PresentationA QC And Benchmark Study Of LC-MS/MS Methods Among MS Laboratories
The ABRF Workflow Interest Network (WIN) A new research group, the Workflow Interest Network (WIN), was established in 2016. Our current focuses are 1) to collaborate with other ABRF members and mass spectrometry-based research groups to identify key factors that contribute to poor reproducibility and inter-laboratory variability, and 2) to propose benchmarks for MS-based proteomics analysis as well as quality control procedures to improve reproducibility.
Current Members Of The WIN Group Emily Chen (Chair) – Columbia University LeeAnn Higgins – University of Minnesota Theresa McLaughlin – Stanford University Achim Treumann – Newcastle University Sheng Zhang – Cornell University Allis Chien (EB Liaison) – Stanford University
Proposed Research Study 2016– 2017: A QC & Benchmarke Study Among MS Laboratories C18 Simple To Implement MS Data Acquisition Repeatability & Reproducibility Data Acquisition Mass Spectrometer Cost Effective Causative & Predictive
MS Core Facility QC Procedures Questionnaire Results https://www.surveymonkey.com/r/H5F3Q5P Q2: Q1:
MS Core Facility QC Procedures Questionnaire Results Q3: https://www.surveymonkey.com/r/H5F3Q5P Q4:
MS Core Facility QC Procedures Questionnaire Results Q5: Q6:
MS Core Facility QC Procedures Questionnaire Results Q8: Q7: https://www.surveymonkey.com/r/H5F3Q5P
Proposed Research Study 2016– 2017 : Two Phases Phase 1 Study: The goal was to examine the LC-MS/MS performance among 11 MS-based core laboratories, using two sets of peptide standards and a complex lysate. Phase 2 study will be launch shortly after the ABRF meeting. An announcement will be made via email. We need your participation!
Proposed Research Study 2016– 2017: Phase 1 Design 2. RT standard 15 peptide mix (10fmole) 15 min x 5 = 200 min 3. Digested Hela lysate + RT peptides (100ng + 10fmol) 100 min (suggested gradient) • Clean and calibrate the instrument & Clean the column 4. RT standard 15 peptide mix (10fmole) 15 min 6. Digested Hela lysate + RT peptides (100ng + 10fmol) 100 min (Lab gradient) 7. RT standard 15 peptide mix (10fmole) 15 min 5. Blank (1ul H2O) – 15 min (same gradient) 8. Submit raw files
Proposed Research Study 2016– 2017: Phase 1 Design Suggested LC Gradient For The Peptide Standard a. Thermo RT peptide mix (10fmol) b. Biognosys iRT peptide mix (1:50) 15 minutes
Proposed Research Study 2016– 2017: Phase 1 Design Suggested LC Gradient For The Hela Digested Lysate (100ng) + Spiked-in Peptide Standard
Proposed Research Study 2016– 2017: Questions To Address In Phase 1 Study • Are suggested concentrations of peptide standards and digested HeLa lysate suitable for evaluating the performance of different mass spectrometers in different laboratories? • Is the suggested gradient for digested HeLa lysate suitable for evaluating the performance of different mass spectrometers in different laboratories? • How consistent are the retention time and mass accuracy of a select peptide standard among different laboratories? • What are ID-free parameters that are indicative of LC and/or instrument performance? • What is the reasonable expectation of repeatability within the laboratory and reproducibilityamong different laboratories for a selected QC sample? • Can we build a benchmark for commonly used mass spectrometers for proteomics analysis?
Proposed Research Study 2016– 2017: Participating Labs In Phase 1 Study Participating Labs & Instruments: Orbitrap Fusion/Lumos TribridOrbitrap Elite/Velos Columbia University (Fusion) University of Cornell (Elite) University of Cornell (Fusion) University of Minnesota (Velos) UCD (Lumos) Stanford University (Elite) University of Minnesota (Fusion) University of Minnesota CancerCenter (Velos) University of Minnesota Cancer Center (Fusion) UW Medicine at South Lake Union Proteomics Resource (Fusion & Lumos) QExative PlusTriple TOF 6600 Wayne State University Newcastle University Thermo Demo Lab (CA) UW Medicine at South Lake Union Proteomics ResourceThe Rockefeller University (Laboratory of Cellular and Structural Biology)
Proposed Research Study 2016– 2017: Phase 1 Study Q1: Are suggested concentrations of peptide standards and digested HeLa lysate suitable for evaluating the performance of different mass spectrometers in different laboratories? Raw File From The Instrument QuiC from Biognosys
Proposed Research Study 2016– 2017: Phase 1 Results ID-Independent Matrices
Proposed Research Study 2016– 2017: Phase 1 Study Q1: Are suggested concentrations of peptide standards and digested HeLa lysate suitable for evaluating the performance of different mass spectrometers in different laboratories? Fusion/Lumos (Retention Time) Lab 4 Lab 6 Lab 2 Lab 1-ref Lab 5 Lab 3
Proposed Research Study 2016– 2017: Phase 1 Study Q1: Are suggested concentrations of peptide standards and digested HeLa lysate suitable for evaluating the performance of different mass spectrometers in different laboratories? Fusion/Lumos (Mass Accuracy) Lab 4 Lab 5 Lab 6 Lab 1-ref Lab 2 Lab 3
Proposed Research Study 2016– 2017: Phase 1 Study Q1: Are suggested concentrations of peptide standards and digested HeLa lysate suitable for evaluating the performance of different mass spectrometers in different laboratories? Elite/Velos (Retention Time) Lab 2 Lab 3 Lab 4 Lab 1-ref Lab 5
Proposed Research Study 2016– 2017: Phase 1 Study Q1: Are suggested concentrations of peptide standards and digested HeLa lysate suitable for evaluating the performance of different mass spectrometers in different laboratories? Elite/Velos (Mass Accuracy) Lab 1-ref Lab 2 Lab 3 Lab 4 Lab 5
Proposed Research Study 2016– 2017: Phase 1 Study Q1: Are suggested concentrations of peptide standards and digested HeLa lysate suitable for evaluating the performance of different mass spectrometers in different laboratories? Lab 3 (Fusion) RT view iRT view Lab 2 (Fusion) Lab 1-ref (Fusion) Lab 1-ref (Fusion) Lab 2 (Fusion) QuiC from Biognosys Q3: How consistent are the retention time and mass accuracy of a select peptide standard among different laboratories?
Proposed Research Study 2016– 2017: Phase 1 Study Q3: How consistent are the retention time and mass accuracy of a select peptide standard among different laboratories? iRT only iRT + Hela iRT only iRT + Hela TIC view iRT view QuiC from Biognosys Lab 1 Fusion Lab 2 Velos Lab 3 Elite Lab 4 Velos Lab 5 Fusion Lab 1 Fusion Lab 2 Velos Lab 3 Elite Lab 4 Velos Lab 5 Fusion
Proposed Research Study 2016– 2017: Phase 1 Study Q3: How consistent are the retention time and mass accuracy of a select peptide standard among different laboratories? iRT only iRT + Hela iRT only iRT + Hela FWHM MS1 Mass Accuracy QuiC from Biognosys Lab 1 Fusion Lab 2 Velos Lab 3 Elite Lab 4 Velos Lab 5 Fusion Lab 1 Fusion Lab 2 Velos Lab 3 Elite Lab 4 Velos Lab 5 Fusion
Proposed Research Study 2016– 2017: Phase 1 Results ID-dependent Matrices
Proposed Research Study 2016– 2017: Phase 1 Study Q2: Is the suggested gradient for digested HeLa lysate suitable for evaluating the performance of different mass spectrometers in different laboratories? Lab5: A Lab5: B Lab1: A Lab1: B Lab2: A Lab2: B 2174 100ng Digested Hela lysate Fusion/Lumos A: suggested gradient B: lab gradient 2774 359 349 2849 2797 3205 3133 3332 3250 2488 2519 2224 2320 2531 3186 2486 Lab6: A Lab6: B 100ng Digested Hela lysate QE Plus >90% Repeatability Lab4: A Lab4: B Lab3: A Lab3: B Lab7: A Lab7: B
Proposed Research Study 2016– 2017: Phase 1 Study Q2: Is the suggested gradient for digested HeLa lysate suitable for evaluating the performance of different mass spectrometers in different laboratories? Lumos Fusion Lab2: Lab Gradient Lab3: Lab Gradient Lab2: Suggested Gradient Lab3: Suggested Gradient QE Plus Elite Lab5: Lab Gradient Lab4: Lab Gradient Lab5: Suggested Gradient Lab4: Suggested Gradient Q5: What is the reasonable expectation of repeatability within the laboratory and reproducibility among different laboratories for a selected QC sample? 56% - 90%
Proposed Research Study 2016– 2017: How Will We Use The Big Data? Polynomial Regression Analysis: log(Number of ID spectra) versus log(Max ms2 injection time) The regression equation is log(Number of ID spectra) = 15.53 - 2.323 log(Max ms2 injection time)+ 0.1827 log(Max ms2 injection time)^2 S = 0.272650 R-Sq = 82.4% R-Sq(adj) = 78.9% Analysis of Variance Source DF SS MS F P Regression 2 3.48143 1.74072 23.42 0.000 Error 10 0.74338 0.07434 Total 12 4.22481
Proposed Research Study 2016– 2017: How Will We Use The Big Data? Q6: Can we build a benchmark for commonly used mass spectrometers for proteomics analysis? *100ng Digested Hela lysate Top 50% Top 50% Top 50% Bottom 20% 2797 proteins Bottom 20% 2021 proteins Bottom 20% 2224 proteins Top 20% 3332 proteins Top 20% 2230 proteins Top 20% 2531 proteins Performance Meter Fusion/Lumos Performance Meter Velos/Elite Performance Meter QE Plus
ACKNOWLEDGEMENT Special Thanks to WIN members Phase 1 Participating Labs EB Liaison – Allis Chien ABRF We need more WIN members! Please participate in the phase 2 study! • The Biognosys Team • Fadi Abdi • Ian Lienert • Florian Marty • Caitlin Needel