Top Down Mass Spectrometry on a Proteomic Scale? - The Protein … · 2013. 7. 9. · Summary and...
Transcript of Top Down Mass Spectrometry on a Proteomic Scale? - The Protein … · 2013. 7. 9. · Summary and...
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Top Down Mass Spectrometry on a Proteomic Scale?
Neil L. Kelleher
Department of Chemistry and
The Center for Top Down Proteomics,
University of Illinois at Urbana-Champaign
November 18, 2004
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The Top Down
Approach
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100% “sequence coverage” at the Intact Protein Level
Gas Phase Fragment Ions (contain a terminus)
N C
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Top Down vs. Bottom Up Approaches to DNA-Predicted Protein Sequence Analysis
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Automating Top Down: Methods
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1. “Front end” Separations and Protein Processing
2. Automation of a Quadrupole-FTMS Hybrid
3. “Back end” data processing and informatics: ProSight PTM
Development of A General Measurement Platform for Intact Proteins and Their Post-translational
Modifications
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A Platform for Top Down Proteomics: Separations, MS Engine, and Informatics
Beckman Coulter2D Proteome Fractionation
PF 2D
AdvionBioSciencesNanoMate 100
Quadrupole (Ion trap) / FT Hybrids
MS/MS Engine
ProSight PTMProtein
Characterization& Bioinformatics
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The Measurement Challenge for Proteomics of Mammalian Cells
XPi
polymorphisms
CN
N-terminal processing(in vivo halflife)
UnexpectedModifications
KnownModifications
Intron/exonBoundaries (?)
Ac Me
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Taylor, Kim, Forbes, Meng, McCarthy, and Kelleher, Anal. Chem., 2003, 75, 4081-4086.
Populating ProSight PTM with known and predicted
biological information
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Shotgun Annotation of a Diverse Protein
Correct Gene Family
Correct Gene
Correct Protein Form
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FTMS for Top Down
•100% Sequence coverage
•High Resolution
•Low ppm mass acuracy
•Whatever else neil wants to talk about
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Automating Top Down: A Custom 8.5 T Q-FTMS
Dana Robinson
Nanospray Robot
Capillary/ Source
Quadrupole/ Collision Octopole
Transfer Octopoles
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Automated Isolation of a 12 kDa Yeast Protein
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Automated Fragmentation of a 12 kDa Yeast Protein
Probability Score = 4 x 10-10
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The PF 2D System
Separate Proteins based on pI, followed by Hydrophobicity
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Studies Underway in the Kelleher Laboratory
• Methanosarcinaacetivorans– CO vs. CH3OH
metabolism• Yeast
– aerobic vs. anaerobic growth (O2 vs. N2)
• Human HeLa cells– Nuclei from
synchronized cells, different stages of cell cycle
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Methanosarcina Acetivorans
- 5,751,492 base pairs - ~4500 open reading frames, - Average coding region ~936
-76% genome for coding-49% predicted protein regions
- 20% predicted hypothetical sequences- 31% no known similarities to other species
-Genetically, physiological and environmentally diverse – large gene families adapt in different
environments (generalist strategy)J. E. Galagan, et. al., Genome Research, 2002, 12, 532-542.
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PF2DpH 8.5
pH 4.0
RPLC Fraction 2
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RPLC Fraction 2RPLC 15MA1083aMA1083bMA1259MA1088
RPLC 16MA1081
MA0646?MA4113?
RPLC 17MA1079MA1350
MA0308?MA1369
MA0483?
RPLC 18MA1071MA0828
RPLC 19MA1110MA3195MA4099MA1077 RPLC 48
MA3737
RPLC 20MA3580?MA1296
RPLC 21MA4547
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HPCF Chromatogram on Yeast Lysate
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HPCF Fraction #3 pH>8.7
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RPLC #7 from HPCF Fraction #3
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Ribosomal Protein 60S L19
Ribosomal Protein 60S L13A
Ribosomal Protein 60S L2
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ESI FTMS of PF2D Sample
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Recent HPCF Chromatogramof Human Nuclei (HeLa cells)
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HPCF-1314-RPLC-01-06
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Automated MS/MS of Low Abundance Species
18+ charge state theo 13955.85-0exp 13997.81-0 ∆m=42.01 ±0.02 Da
SWIFT
ECD
Broadband
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Simultaneous Characterization of a PTM, cSNP, and Gene Family Member
Mix
Auto-ECD …of a 8% component
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Automated Data Analysis:Finding Monoisotopic Masses of Fragment Ions
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ProSight PTM
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Click Here
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ThresholdMS/MS
(b/y)
Electron-basedMS/MS(c/z•)
Integration of Threshold and Electron Fragmentation Approaches for Intact Protein Characterization
Top Down Fragmentation Data
Absolute fragmention masses
(e.g., 2369.65 Da, 4567.56 Da,
8763.23 Da, ...)
Protein Identification
Protein Characterization
“Sequence Tags” (e.g., ...EVPDG...)
Explanation of ∆m’s
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From One Gene, Many Protein Forms: A Major Theme in Contemporary Proteomics
DNA
Gene Family,coding SNPs
Alternativesplicing
mRNA Protein
CovalentModification
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“Shotgun Annotation” of Biological Variation: Over-Population of “Post-Translational Space”
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Summary and Outlook• Throughput for Top Down Analysis of Proteins and Protein Mixtures is increasing with the advent of more intelligent automation tools and strategies
• Top Down Protein Analysis is capable of simultaneousGene-Family, SNP, and PTM determination “Shotgun Annotation” for human proteins
• Top Down is extendable to non-mass spectrometristsowing to high specificity and full characterization
• IEF and Chromatofocusing is perhaps the best current answer to the Protein Processing Problem for Top Down MS
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Acknowledgements
Leah MillerYi Du
Shaun McLoughlinJim Pesavento
Lihua JiangLeslie Hicks
Jon FergusonMichael BoyneMichael Roth
Dana RobinsonPaul Thomas
Kelleher Group
Fiscal SupportPackard, Burroughs Wellcome, Searle, Sloan, Res. Corp. Cottrell
NIH (GM 067193), NSF CAREER
Seyoung SohnTom Junysk
Comp. Sci. (Undergrad.)
Dr. Eric ThomasDr. Pieter Dorrestein
Post. Doc.
Ben CargileJeff Johnson
Dr. Jay CharleboisDr. Fanyu MengDr. Steven Patrie
Dr. Andrew ForbesDr. Karen Topp
Dr. Matthew MazurGreg Taylor Lee Bynum
Joe SolaAndrew Birck
Comp. Sci. (Grad.)
Yong-bin KimRich LeducIan Brooks
Former
Nicole FrielJosh Norris
Undergrad.
DatabasesGeneva Belford
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https://prosightptm.scs.uiuc.edu