# Presentation: 238689

## Kelleher Lab Overview

***Kelleher Lab Overview***

**Instrumentation /Bioinformatics**

**Mass Spec.-Based**
**Enzymology**

**The Histone Code**

**MS/MS**

**FTMS**

**“****Top Down” Proteomics**

## Why a Chemist needs Computer Science, Biology and Engineering to Push the Limits of Modern Mass Spectrometry

**Neil Kelleher **
***University of Illinois at Urbana-Champaign***
**Department of Chemistry**
**Fermi Teacher Workshop**
**Feb. 27, 2004**
**Fiscal Support ******** NSF and Cottrell Scholars**

## Top Down vs. Bottom Up Approaches to Post-Genomic Protein Analysis

## Interdisciplinary Teams

**Chris Hendrickson**

**Mark Emmett**

**John Quinn**
**Greg Blakney**

**(NSF, State of Florida)**

**Alan Marshall**

**Interdisciplinary Teams**

**Steven Patrie **
**Leah Miller**
**Andrew Forbes**
**Matthew Mazur**
**Yi Du**
**Shaun McLoughlin**
**Jim Pesavento**
**Lihua Jiang**
**Leslie Hicks**
**Michael Boyne**

***Kelleher Group***

***Key :***
***Red ************ Biology        ******Blue ************ Computer Science***
***Black ************ Chemistry, Bioanalytical***

**Packard, Burroughs Wellcome, Searle, Sloan, Cottrell**
**Eli Lilly, Abbott, Waters**
**NIH (GM 067193 + GM 067725), NSF CAREER**

**Joe Sola**
**Dana Robinson**
**Andrew Birck**
**David Whipple**
**Tom Junysk**

*Comp. Sci. (Undergrad.)*

_**Histones**_

**Craig Mizzen**

**Eric Thomas**

*Post. Doc.*

**Ben Cargile**
**Jeff Johnson**
**Dr. Jay Charlebois**
**Fanyu Meng**

*Comp. Sci. (Grad.)*

**Greg Taylor **
**Yong-bin Kim**
**Rich Leduc**
**Ian Brooks**

*Former*

**Carl Lindberg**

*Undergrad.*

**NCSA**

## Outline

- New Course at the University of Illinois (Chemistry)
- Background and Scope of Contemporary Mass Spectrometry in Proteomics
- New-ish Developments, Applications, and Illustrations
- Latest, Greatest from the Kelleher Lab Top Down Proteomics, a New Frontier in Mass Spectrometry

## CHEM/BIOCH 473Genomics, Proteomics, and Bioinformation:  A Survey of Modern BioAnalytical Methods

***When:***  Spring 2004;  Tues / Thurs.  4 - 5:20 pm  in  162 Noyes Lab.
***Instructor:***   Neil Kelleher
***Credits:  ***0.75 Units / 3 hours  (or 1 U / 4 hours with extra project)
***Course Material:***  Genomes, 2nd Edition (Brown) and Primary Literature / Reviews
***Assumed Background Knowledge:***  Structure of DNA, RNA, and proteins and the basics of Replication, Transcription, and Translation in Bacteria, Archaea, and the Eucarya

## Course Outline

1.  Genomics:  From Sequencing to Variation
	A.  Strategies and Technologies for Genome Mapping and Sequencing
	B.  The Human Genome:  How’d they do it?  (Public vs. and Private)
	C.  Polymorphisms

2.  Transcript Profiling.
	A.  DNA chips
	B.  “Genome” Arrays
	C.  Do mRNA levels correlate with protein levels?

3.  On the Protein Level.
	A.  2-D gels, “Classical” Proteomics
	B.  Quantitative and Functional Proteomics
	C.  Proteome Analysis in microorganisms and mammals
	D.  Differential Post-translational Modification

4.  Disease:  Gene Hunting and Biomarkers.
	A.  SNPs, Positional Cloning, and Linkage (Disequilibrium).
	B.  Biomarker Discovery and Validation 

**1.  Genomics:  From Sequencing to Variation**
- 	A.  Strategies and Technologies for Genome Mapping and Sequencing
- 	B.  The Human Genome:  How’d they do it?  (Public vs. and Private)
- 	C.  Polymorphisms
**2.  Transcript Profiling.**
- 	A.  DNA chips
- 	B.  “Genome” Arrays
- 	C.  Do mRNA levels correlate with protein levels?
**3.  On the Protein Level.**
- 	A.  2-D gels, “Classical” Proteomics
- 	B.  Quantitative and Functional Proteomics
- 	C.  Proteome Analysis in microorganisms and mammals
- 	D.  Differential Post-translational Modification
**4.  Disease:  Gene Hunting and Biomarkers.**
- 	A.  SNPs, Positional Cloning, and Linkage (Disequilibrium).
- 	B.  Biomarker Discovery and Validation

## Ionization Methods

- Electron Impact (EI)
- Field Ionization (FI)
- Field Desorption (FD)
- Chemical Ionization (CI; also APCI)
- Fast Atom Bombardment (FAB)
- Matrix-Assisted Laser Desorption Ionization (MALDI)
- Electrospray Ionization (ESI)

**Increasing “Softness”**

## Matrix-Assisted Laser Desorption Ionization (MALDI)

- Laser

- Franz Hillenkamp and Michael Karas, 1988

**Matrix-Assisted Laser Desorption Ionization (MALDI)**

**Notes:**
The SELDI process graphicall looks like this.  1microliter of Crude biological sample added to the chip and the proteins of interest are captured on the appropriate chemical, biochemical or biological affinity capture surface; then, the unwanted sample material is washed away.
A laser is used to read the retained proteins which are desorbed and ionized by multiple pulses of laser and detected.  The molecular weight of each protein is deduced by the software and displayed as shown.  The homogeneous nature of the surface provides excellent quantitative results.

Retained proteins can be further processed directly on the chip for sequence, post translational modification, protein interaction studies, or higher resolution protein expression analysis.

## Anatomy of ESI

- From Kebarle & Tang, *Anal. Chem*. 1993, **64**, 972A

## Conventional ESI

## Anatomy of ESI

## Operating Principles

- No pumps - flow is generated by the electrostatic “pressure”
- Flow rate is function of:
- Tip Size
- Applied Voltage
- Tip-Inlet Distance

- Plume @ 60 nL/min

## Typical Electrospray Sources

## Kelleher, N. L. “From Primary Structure to Function:  Biological Insights from Large Molecule Mass Spectra.” Chem. Biol. 2000 Feb; 7; R37-R45.

- Kelleher, N. L. “From Primary Structure to Function:  Biological Insights from Large Molecule Mass Spectra.” *Chem. Biol.* **2000** Feb; *7*; R37-R45.

## The ESI tip of a miniature chromatographic column

- Pack the LC column directly into the tip!
- “Zero” post column volume

## Courtesy, David Muddiman

## Human Genome Project 

**Human Genome Project**** **
**WGSA and NCBI-34**
**Assemblies**

**Source: **http://www.pbs.org/faithandreason/bio/coll-frame.html

## Whole Genome Shotgun Sequencing

**Genome with Unknown Sequence**

**Reconstructed Genome Sequence**

**DNA Fragments**

## A Revised Phylogentic Tree of Life

**A Revised Phylogentic Tree of Life**

- How does gene number and gene product complexity scale across the tree of life?

## From One Gene, Many Protein Forms: A Major Theme in Eukaryotic Proteomics

**DNA**

**SNP**

**~30,000 human genes**

**>100,000 RNA messages**

**>1,000,000 distinct protein forms**

## Protein Primary Structure...

## The Proteome – A Definition

- - Every gene product expressed (>1 copy number) at a given time, in a given cellular state

_**What information about Proteins do we want ?**_
- Identity
- Absolute Abundance (copy #)
- Relative Abundance (2 cellular states)
- Post-translational State
- Biochemical Activity (Function)
- Non-covalent Associations
*in vivo *half-life
- Sub-cellular Localization

## 2D Gel Electrophoresis

**2D Gel Electrophoresis**

- De Novo Sequencing Possible

## Peptide Mapping:  Match peptide MW Values Up with Corresponding regions of Predicted amino acid Sequence

- Peptide Mapping:  Match peptide MW Values Up with Corresponding regions of ***Predicted*** amino acid Sequence

- _An Example Peptide Match:_
- expt’al MW = 1346.79 Da
- Theor. MW = 1346.82 Da

**Treat with protease **
**(usually trypsin)**

- Sequence Coverage typically 5-50%

## Protein Identification by 2D Gel and 

**Protein Identification by 2D Gel and **
**Tandem Mass Spectrometry**

- Gygi *et al*. Mol. Cell Bio. (1999)

## Tandem Mass Spectrometry (MS/MS)

**MS - I**

**MS - II**

**Current Fragmentation **
**Methods Use ...**
**-  collisions with gas (major)**
-   infrared lasers
-   electrons

## Slide 30

## Identification of the 15 kDa band by mass spectrometry.Part of the mass spectrum of the peptide mixture obtained after digestion of the protein band. (Data from M. Mann, PNAS, 1996) 

## 2D Gel Electrophoresis

**2D Gel Electrophoresis**

- Dynamic Range Problem !

- - cut out each spot
- - Digest with Trypsin Protease
- - load onto  MALDI target or micro-LC column (ESI)

## Landmarks in Proteomics

- Mid/Late-1980’s:  de novo sequencing of >300 aa proteins possible (K. Biemann, MIT)
- 1991:  Identification of a protein using the mass of its tryptic peptides (J. Stults, Genentech)
- 1993:  Miniaturization of Electrospray Ionization...”Nanospray” (M. Mann, EMBL Heidelberg; also Emmett/Caprioli, “Microelectrospray”)
- 1994:  Term “Proteomics” coined by Marc Wilkins
- 1994:  Peptide Sequence Tags formalism introduced (M. Mann)
- 1995:  Unattended Protein i.d. Using Sequest (J. Yates, Univ. Of Wash.)
- 1996:  Mann extends protein i.d.’ing to protein complexes (“Functional Proteomics”; 1-D gels)

## Proteomic Landmarks (continued)

- 1996:  Mann demonstrates large scale use of 2-D gels with MS-Based Protein i.d.’ing using Yeast (~200 proteins);  gels give abundance info. and Mass Spec. Identifies proteins
- 1999:  Yates bypasses gels using “Shotgun Proteomics”
- 1999:  Aebersold bypasses gels for determination of relative protein abundance (the “ICAT” Method).
- 2000:  Move toward monitoring differential Post-translational Modifications (B. Chait, Rockefeller, Aebersold, Univ. of Wash.)
- 2002: “Large Scale” analysis of Protein Complexes by Affinity Chromatography - nLC-MS/MS (Cellzome, MDS Proteomics)
- 2004:  Peptide-driven Mass Spec. platforms can identify 1000’s of proteins per week;  Intact Protein Analysis viable on a large scale (Kelleher Group)

##  “Classical” Proteomics

- Sequence Coverage typically 5-50%

*Sequence predicted*
*from the Genome.*

-  **Contemporary Advances**

**N**

**C**

***Non-gel ESI/MS/MS      Approaches (ICAT, “Shotgun Proteomics”)***

-  “...the mass spectrometric identification and quantitation of posttranslational modifications [is] largely [an] unsolved problem in high-throughput proteomics.”

**-  ****Matthias Mann****  **(*Nat. Biotechnol.***, ****1999**,** ***17*, 954-955.)

## Top Down vs. Bottom Up Approaches to Post-Genomic Protein Analysis

## The Top DownApproach

***The Top Down******Approach***

## “monoisotopic”

***“******monoisotopic”***
***peak***

***“******chemist’s ***
***average” ***

***“******most abundant” ***
***isotope peak***

## Slide 39

## Slide 40

## Slide 41

## Two General Ways to Fragment Gas Phase Ions

## 1.  “Front end” Separations: ALS-PAGE/RPLC2.  Automation of a Quadrupole-FTMS Hybrid3.  “Back end” data processing and informatics:   			ProSight PTM

**Development of A General Measurement Platform for Post-translational Modifications**

## Overview of Sample and Data Flow Through the Illinois Measurement Platform

**Overview of Sample and Data Flow Through the Illinois Measurement Platform**

## General Platform for Analyzing Intact Proteins

- Meng, Cargile, Patrie, Johnson, and Kelleher, *Analytical Chemistry*, **2002**, *74*, 2923-2929.

- Good For Proteins <70 kDa and >1000 copy number (yeast)

## Q-FTMS

**Q-FTMS**

***Data Dependent Isolation***

***Robust Fragmentation***

***An “Answer”***

## Automated ESI/Q-FTMS/MS of yeast proteins

**F. Meng, S. Patrie**

## A Quantitative Model for “Top Down” Database Search Specificity

* **f * is the # of input fragment ions,
* **n* is the # of spurious matches,
***M******a*** is the Mass Accuracy

- F. Meng, B. Cargile, L. Miller, J. Johnson, and N. Kelleher*, Nat. Biotechnol.*, **2001**, *19*, 952-957.

**Probability of a Spurious     ****	****Protein Match**

**=**

**‘*****P score*****’ = P*****f,n***** =**

**(*****xf*****)*****n***** **x** *****e******-xf***

***n!***

***x***** = mean = 1/111.1 **x** 2 **x** M****a**** **x** 2**

## Slide 49

## 4 levels of biological variation...

- Gene family
- Polymorphisms /mutations
- Alternative splicing (RNA editing too)
- PTMs

## Identifying a SNP Product and N-Term PTM in one Sample

**Identifying a SNP Product and N-Term PTM in one Sample**

**Known SNP, val9ile *********m *****= 14.02 Da**
**Pscore 4****	****   ****Pscore 4 x 10****-7**
**1 c     3 z****●**** ****	****   ****6 b 10 y**

**New N-terminal acetylation, *********m*****= 42.2**
**Pscore ****1 x 10****-12****   ****Pscore 9 x 10****-11**
**8 c     19 z****●****         ****6 b 11 y**

**CAD**

**CAD**

**9+ charge state**
***theo***** 6657.6-*****0***
***exp  *****6657.8-*****0***

**13+ charge state**
***theo***** 11601.8-*****0***
***exp  *****11644.0-*****0***

## Shotgun Annotation of PTMs:  Over-Population of “Post-Translational Space”

## Slide 53

## “Shotgun Annotation” of Histone Modifications

## Slide 56

## Human Histone H4

## A Histone-Only database, with heavy PTM annotation.

**A Histone-Only database, with heavy PTM annotation.**

_**S**_G_**R**__**3**_G_**K**__**5**_GG_**K**__**8**_GLG_**K**__**12**_GGA_**K**__**16**_RHR_**K**__**20**_VLRDNIQGITKPAIRRLARRGGVKRISGLIYEETRGVLKVFLENVIRDAVTYTEHAKRKTVTAMDVVYALKRQGRTLYGFGG

**Query  database of all possible**

**PTMs at known modifiable sites**

**DB with 46,875 **
**protein forms**
**(7.8 MB)**

**Generate list of 91 fragment ions**

**MS/MS of ****+112 Da**** Species of Histone H4:**** **

**“****The Answer” ...**

**(107 scans)**

**Pesavento, Kim, Taylor**

## Output from Database Retrieval at 5 ppm

** ****N-terminal**** acetylation**
** ****K16**** acetylation**
** ****K20**** di-methylation**
_***Results***_***: 78 c/z*****.***** fragment ions match up at <5 ppm***
***(results confirmed manually)***

## Human Histone H4

## Summary and Outlook

-   **Tailored software for Top Down MS Exists NOW:   **_**https://prosightptm.scs.uiuc.edu**_**      ****(...SNPs, PTMs in databases)**
-   **An Integrated Platform for Top Down Proteomics now Exists: proteome processing, Q-FTMS Engine, and Software**
**  ****Top Down Analysis of Proteins and Protein Mixtures will become more routine (new wave of commercial instruments)**
**    ****Can *****Directly *****Identify Putative “Biomarkers” from body fluids with Top Down Mass Spectrometry ******** diagnostics for disease**

## Acknowledgements

**Chris Hendrickson**

**Mark Emmett**

**John Quinn**
**Greg Blakney**

**(NSF, State of Florida)**

**Alan Marshall**

**Acknowledgements**

**Steven Patrie **
**Leah Miller**
**Andrew Forbes**
**Matthew Mazur**
**Yi Du**
**Shaun McLoughlin**
**Jim Pesavento**
**Lihua Jiang**
**Leslie Hicks**
**Michael Boyne**

***Kelleher Group***

**Joe Sola**
**Dana Robinson**
**Andrew Birck**
**David Whipple**
**Tom Junysk**

*Comp. Sci. (Undergrad.)*

_**Histones**_

**Craig Mizzen**

**Eric Thomas**

*Post. Doc.*

**Ben Cargile**
**Jeff Johnson**
**Dr. Jay Charlebois**
**Fanyu Meng**

*Comp. Sci. (Grad.)*

**Greg Taylor **
**Yong-bin Kim**
**Rich Leduc**
**Ian Brooks**

*Former*

**Carl Lindberg**

*Undergrad.*

**NCSA**

***Fiscal Support***

**Packard, Burroughs Wellcome, Searle, Sloan, Cottrell**
**Eli Lilly, Abbott, Waters**
**NIH (GM 067193 + GM 067725), NSF CAREER**

## Slide 63