•Peak capacity exceeding 800.
•Deeper proteome coverage with a consistent 5700 protein groups per run.
•9% increase in protein groups over 3 combined runs compared to 50 cm column.
•Identify more proteins per hour – comparable identifications in 120 minutes to a 50 cm column in 240 minutes.
• More quantifiable proteins 50% increase in the number of quantifiable proteins with CVs <5%
•Take advantage of segmented quadrupole (QE Plus and HF), for more efficient isolation in narrow windows
•Pre-fractionation recommended for high complexity samples to improve quantification accuracy and precision (Pierce Spin Column)
Data Analysis
Proteome Discoverer 2.1
•New method TMT quantification
•TMT correction factors (for all TMT reagents) with new user interface
•Use of “Razor” peptides for protein quantification
•Modified form of Gygi group’s S/N-based approach to TMT quantification
•Custom ratio generation
•New heat map-like coloring of ratios and scaled abundances
Note that almost of all these changes are also applied to isotope-labeled quantification (e.g. SILAC)
TMT Correction Factor Setup
TMT correction factor certificate for each manufacturing lot
Edit Quantification Method
Study Management Setup
•Select quan method and assign study factors
•Input data
•Specify how to group quantification results
•Specify Quan method, match data files and Quan Channels with study factors
•Select processing and consensus workflows and make modifications
•Run
Accommodates the most complex study designs
Select Workflows and Modify Parameters
Select Workflows and Modify Parameters (Con’d)
New Custom Ratio Calculation in PD 2.1
Grouping and Quantification
Results From Biological Replicate Search
•Replicates grouped into ratios + standard errors
Zoomed Ratios and Scaled Abundances
Summary
Comprehend
the fundamentals of isobaric labelling and the dramatically increased throughput enabled by multiplexed quantitation as well as the ease of sample preparation
Configure
an LCMS method for the high accuracy quantitation of TMT labeled samples using the Orbitrap Fusion Lumos with SPS MS3 with the ideal settings
Quantify
peptides labeled with TMT using Proteome Discoverer 2.1 using SequestHT and MS3 quantitation.
Advocate
the complete workflow from sample preparation to data analysis for the multiplexed quantitation of complex samples using TMT and the highly differentiated SPS MS3 on the Orbitrap Fusion Series Instruments
Additional Resources
•Online Resources
•http://portal.thermo-brims.com/ (Software, Manuals, Tutorial Help Videos, Discussion Forum.)
•http://planetorbitrap.com/ (Published Articles, Posters, Brochures, Product Support Bulletins, Technical Guides, Webinars, Protocols, Application Workflows.)
•Some More Publications
Relative Quantitation of TMT-Labeled Proteomes - Focus on Sensitivity and Precision
Viner R, Scigelova M, Zeller M, Oppermann M, Moehring T, Zabrouskov V.
Application Note 566
Increasing the multiplexing capacity of TMTs using reporter ion isotopologues with isobaric masses
McAlister GC, Huttlin EL, Haas W, Ting L, Jedrychowski MP, Rogers JC, Kuhn K, Pike I, Grothe R, Blethrow JD, Gygi SP.
Anal Chem. 2012 Sep 4;84(17):7469-78.
MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics
Ting L, Rad R, Gygi SP, Haas W.
Nat Methods. 2011 Oct 2;8(11):937-40.
Evaluating multiplexed quantitative phosphopeptide analysis on a hybrid quadrupole mass filter/linear ion trap/orbitrap mass spectrometer
Erickson BK , Jedrychowski MP, McAlister GC, Everley RA, KUNZ R, Gygi SP
Anal Chem.2015 Jan 20;87(2):1241-9.
Acknowledgements
•Thermo-Life Sciences
•Ryan Bomgarden
•Sergei Snovida
•Paul Haney
•John Rogers
•Thermo-LSMS
•Rosa Viner
•Xiaoyue Jiang
•Michael Blank
•Andreas Huhmer
•Graeme McAllister
•Tabiwang Arrey
•Vlad Zabrouskov
•Michaela Scigelova
•David Horn
•Torsten Ueckert
•TMT Collaborators
•Steve Gygi, Harvard Medical School
•Josh Coon, University of Wisconsin, Madison
•Jennifer Van Eyk, Johns Hopkins School of Medicine
•Zezong Gu, University of Missouri-Columbia
•Kay-Hooi Khoo, Academia Sinica
•Bernhard Kuster, Technische Universität München
•Somi Afiuni & Tim Griffin, University of Minnesota