Mass Spectrometry in the UVa Core

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Mass Spectrometry in the UVa Core
Nicholas E. Sherman, Ph.D. Research Associate
Professor of Microbiology Director W.M. Keck
Biomedical Mass Spectrometry Lab nes3f_at_virginia.ed
u

• December 12th 2006
• Charlottesville, VA

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Highlights of the UVa MS Core

• New instrumentation
• Varied sample formats
• Quantification services
• PTM analysis
• Bioinformatics

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New Instruments

• Thermo Electron LTQFT
• 400K resolution, 0.5-3ppm mass accuracy
• Hybrid features allow MS and MS/MS at same time
• Addition of ECD fragmentation
• Applied Biosystems QSTAR Elite
• 20K resolution, 10-20ppm mass accuracy
• Different fragmentation patterns from ion traps
• Resolution and mass accuracy in MS/MS
• Thermo Electron LTQ
• Addition of ETD fragmentation

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Sample Types

• Gels
• Solutions LC, affinity, IP, etc.
• Tissue
• Media

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Tissue Samples

• Extensive gene expression profiling of 80
  tobacco-associated squamous carcinomas of the
  lung and head neck has yielded a potential
  biomarker (C. Moskaluk)
• Objective Extend this work to protein analysis
  to
• Validate candidate biomarker
• Discover new biomarker proteins
• Develop new methods applicable to other research
• Tissue Analysis Strategy
• Take advantage of large repository of archived
  tissue specimens
• Need a to extract proteins from formalin-fixed
  paraffin-embedded (FFPE) samples
• Initial Approach
• Laser capture microdissection of frozen and FFPE
  specimens
• Protein extraction and digestion using EPI kit
• LC/MS/MS sample analysis
• MS data analysis

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LCM Results
Initial Results (30K cell LCM preps)
Scaffold analysis of LC/MS-MS (LTQ-FT) data
acquired from initial FFPE and FR tissue samples
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Media Cross-talk in Invasive Melanoma

• Previously explored effect of co-culture of
  invasive/metastatic and non-invasive/non-metastat
  ic melanoma cell lines with stromal fibroblasts
  using gene expression analysis with microarrays
• It was found that there is a significant
  pro-invasive effect of invasive/metastatic
  melanoma cell lines on fibroblast gene expression
  which was confirmed in invasive human melanoma
• One question is what factors from the melanoma
  signal the stromal fibroblasts to alter their
  gene expression profiles?

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Gene Expression Profile
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Protein Profiling in Media
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Quantification Strategies

• Chemical
• Labeling never complete / interferences
• Compares only 2-8 samples
• SILAC
• Must be able to grow cells
• Compares 2 or 3 samples
• Ion Current
• No labeling of any kind
• Normalization issues
• Can compare many experiments and compounds

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Chemical Labeling

• Chemical modification to amino acid(s) generally
  after digestion
• Most labels differ by 3-10Da in mass
• Deuterium does not co-elute
• C13/N15 does
• Examples include methyl esters, ICAT, ITRAQ

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Chemical Labeling Example(ITRAQ)
MS/MS!
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Quantitation by Ion Current

• 2 separate LC/MS runs are compared
• Matching/loading issues present
• Standards needed (internal or external)
• Robust because no labeling and many samples and
  experimental conditions can be compared
• See everything in the sample not just what gets
  labeled

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SILAC

• Stable isotopes incorporated during cell growth
• Lys (8 Da) and Arg (10 Da)
• Condition 1 (light) and condition 2 (heavy) then
  mix equal amounts and digest
• Ratios reflect relative abundances

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SILAC Example
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How do you know its a binding partner?

• Heavy cells contain tagged bait
• Light cells no bait
• Pre-bind affinity column with light extract
• Add heavy extract
• Affinity purify bait
• Heavy ratio indicates specific binder and light
  ratio indicates non-specific binder

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Binding Partners

• Cortactin 0.051 LH (Bait)
• ARP3 0.211 LH
• AR20 0.301 LH
• Actin 0.311 LH
• Other set predominately light
• List of new proteins predominately heavy New
  Binding Partners

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Post-translational ModificationsPTMs

• Glycosylation
• Phosphorylation
• Acetylation/Methylation
• Ubiquitination
• Sumoylation
• Lipidation aliphatics, isoprenyls, GPIs
• Nitration
• Sulphation

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Broad Keys to PTM Success

• Resolution
• What overlaps?
• Mass Accuracy
• Correct searches?
• Dynamic Range
• lt0.1 found?

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Examples of PTM Analysis

• Ubiquitination studies
• Phosphorylation studies

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Ubiquitination

• Cell cycle regulators need to be degraded
• Cycle must progress in one direction
• How? Ubiquitination (phosphorylation)
• 68 SCF ligases in humans
• Each ligase complex has a different F-box subunit
• ßTrcp (Fbw1 or Fbw11)

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General Method

• HA tagged ßTrcp expressed in HEK293T
• Also expressing FLAG tagged ubiquitin
• Pull down HA
• Take eluate and pull down FLAG
• Elute for MS

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Proteins Found

• Baits
• ßTrcp and Ubiquitin
• SCF subunits
• Cul1 and Skp1
• Known substrates
• ß-catenin, Cdc25A, Wee1, HNRPu
• Potential substrates
• Claspin
• PDCD4

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Claspin Termination of the DNA Replication
Checkpoint
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Claspin Chk1 Cdk1
APC/C
Molecular Cell. 2006. 23319-29.
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PDCD4 Protein Synthesis and Cell Growth
Science. 2006. 314467-471.
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Phosphorylation

• Cell signaling control
• CDKs - family of protein kinases
• Associate with cyclins
• Control of cell cycle and proliferation
• Phosphorylation in activation loop required

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General Method

• GST- or His-CDK2 expressed in E. coli
• Pull down performed
• Eluate run on 1D gel
• Band cut for MS analysis
• Any phosphorylation in a bacterial system???

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PO4 Sites Found

• 1 Ser, 1 Tyr and 1 Thr found phosphorylated
• Levels estimated at the 0.1-2 level
• Thr is the catalytic Thr160 site

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Autocatalytic Phosphorylation of CDK2
JBC. 2006. Submitted.
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Bioinformatics

• Jeff Chen, Ph.D. and post-doc added to core
• Trained in bioinformatics
• Upgrading all systems
• GenoLogics Proteus LIMS
• Automated data and data analysis capture
• Sample tracking, status, etc
• Investigator access
• Links to data generated at EVMS and GMU MS labs
• Expanding later into other information links
• Scaffold Data System
• Unified system for data analysis and display
• Core collaborates on new features
• Free viewer for investigators