Insider secrets to PTM analysis using proteomics mass

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Insider secrets to PTM analysisusing proteomics mass spectrometry

David ChiangChairman, Sage-N [email protected]

Stanford SUMS Meeting, Sept 2, 2010

100902SUMS 2 www.SageNResearch.com

Can we really do these with mass spec?

1. Identify peptides with PTMs?• Phosphorylation• SUMO-ylation• Glycosylation

2. Quantify them?

3. Localize the PTM sites?• Ascore for phospho


* Your mileage will vary. (Helps if the Data God is smiling on you that day.)

*


Incredible potential of ProteomicsExpensiveInstrument

CrypticData Eureka!Tricky

Data Analysis

Mass Spectrometry Protein Spectrum Your Face HereSupercomputer

X-Ray Crystallography DNA Photo 51 Fame & FortuneLots of Paper, Pencils


Agenda

• Overview• PTM data analysis• Scripting capability is key• SORCERER for cancer PTMs


Scientific Advisory Board

John R. Yates, IIIScripps Research Institute

Steven GygiHarvard Medical School

Ruedi AebersoldSwiss Institute of Tech. Zurich

Roman ZubarevUppsala University


Some of Our Customers


Proteomics in Principle: Simple!

1. Prepare clean sample

2. Separate and measure

3. Interpret the data


Proteomics in practice: ‘Food Network’ + ‘CSI’

• Play Chef with sample preparation• Play Detective with data interpretation

Need both very different skill sets for success!


If the FBI did Protein ID …

Basic algorithm (FBI’s AFIS)Step1: Measure Raw Data [MSMS]

– Extract all available finger prints from crime scene

Step2: Search Engine [SEQUEST]– Get top scoring DB hits for each finger print

– Several sub-scores (size, features, correlation of “minutae”)

Step3: Determine True/False Hits [PeptideProphet]– Decide which hits are valid and which are iffy

– Individual hits assigned true/false or probability value

Step4: Infer Suspect [ProteinProphet]– Combine one or more finger/thumb prints back to person

“Q-Tof”

“Ion Trap”


Proteomics Costs & Time(adapted from Mallick & Kuster NBT 7/10)

• How long to get results?• 5-10 working days for simple protein ID and quantitation• 4-6 weeks for quantitative protein expression profiling• 2-6 months for PTM analysis

• How much does it cost?• $50-200 for simple protein ID• $500-2K for simple PTM analysis• $5K-15K for complex PTM analysis• $1K-$2K for quantitative protein expression profiling


Data Analysis for Phosphorylation Profiling

• Search CID spectra with STY +80 Da– Look for intact phosphate

• Tyrosine• Phosphate stabilized near Proline

– Run Ascore algorithm to localize sites if possible

• Search CID spectra with ST -18 Da, precursor -80 Da• Look for phosphate losses during separation

• Search CID MSA/MS3 with precursor -80 Da• Search ETD with STY +80 Da• Other

• HCDAll depend on robust peptide ID foundation.All require some workflow scripting.All require some dataset-dependent detective work.


Other PTMs of Interest

• SUMO-ylation (Small Ubiquitin-like MOdifier)– ~100 residue peptide attached to K in consensus sequence y-K-x-D/E– Scripting required around Search Engine

• Account for PTM fragmentation• Search consensus sequence

• Glycosylation– Scripting for N-linked glycopeptides for consensus sequence N-x-S/T– (See www.Proteomics2.com blog for info 10/08)


Which Quantitation Method?(adapted from Mallick & Kuster NBT 7/10)

Metabolic labeling (eg SILAC, 15N)• Small changes (10-50%) in cell cultures

Peptide labeling (iTRAQ, TMT)• Moderate changes (50-200%) for multiplex experiments (eg time course, dose response)

Label-free using MS1• Moderate changes (50-200%) for comparing many similar experiments

Label-free using spectral counting• Large changes (>100%) for comparing many similar experiments

Single/Multiple Reaction Monitoring (SRM,MRM) with spiked standards(AQUA)

• Absolute quantity in complex sample (eg serum)


Peptide Search Engine = Foundation

AgilentABIBrukerHitachiShimadzuThermoWaters…

TandemMass Spectrometer

PeptideSearch Engine

SEQUEST®

Mascot®

X!Tandem

PHENYX®

OMSSA

ProteinPilot™

ProteinProspector

SpectrumMill

InspecT

…

SCAFFOLDTrans-Proteomic Pipeline

DTASelect, Census

Proteome Discoverer

…

PeptideInference

ProteinInference

…

SEQUEST is a registered trademark of University of Washington. Others are trademarks of their respective owners.

PTM(Ascore)

Quant.(SpecCount)


MASCOTSearch Engine and Protein ID Application

• Relatively simple but extensively-tuned scoringmodel based on PMF

– Unpublished model, but appears to be Ionscore = Max(#Matched m/z’s) x Factor [Factor commonly ~11]

– Ideal for TOF data• Every peak is “significant”, mass-accurate, with no extra peaks

• Search Engine key steps1. From spectrum, derive list of characteristic m/z’s

(peaks are ignored in scoring)

2. Peptide score according to # matched m/z’s vs. theory


SEQUESTSearch Engine Only

• Original search engine, circa 1993– Cross-correlation score (like cell phones etc.)– Compute-intensive, but sensitive– Developed for ion trap data

• Lots of extra peaks, with poor mass accuracy

– Needs post-processing• PeptideProphet, Proteome Discoverer, DTASelect, Scaffold

• Search Engine key steps1. Find top 500 DB entries with good overlap with spectrum

(peaks are considered)

2. Calculate cross-correlation etc., and report top hit(s)


SEQUEST 3Gon Sorcerer

Key Steps:1. Fast but accurate spectrum matching

that uses ppm mass accuracy2. Complete "on the fly" consideration of

chosen PTMs3. All candidate matches (not just a

"short list") get rigorous cross-correlation scores ...

4. ... to enable most sensitive rankingand effective compilation of results

5. Comprehensive XCorrs also allowreliable E-value results for simpleinterpretation, as well as computationof legacy SEQUEST scores


SORCERER Scripting PlatformMUSE = Modular Utilities for Search Engines

• Re-score engines for search results– Ascore phosphorylation site localization– Other similarity scores (e.g. binomial scoring used by Mann, Gygi)– Post-process and filter for decoys, incorrect mods

• Pre-process spectra for search and re-search– Calculate mass shift and re-adjust precursor masses– Compute FDR using different formulas– Mass-accurate MS3 from mass-accurate MS2– Add/subtract 98 Da for phospho searches

• Interactive data query– Run what-if’s quickly on complex search results

• Workflow automation– Auto archive after search


Difference between ‘Script’ and ‘Program’e.g. Microsoft Excel Example

Microsoft Excelis a Program

Customize platform viaVBasic Scripts


SORCERER Script Example:VersaSearch™ for combined CID/ETD

• Unified search accommodates ETD variations• All-CID, all-ETD, alternating, & decision tree

• Peptide terminus mods to account for b vs c, y vs. z-radical• Post-processing to define “true” vs. “decoy”

• Post-search re-scoring provides other similarity scores• E.g. binomial scores• User-defined modules for special PTMs

SEQUEST 3GPeptide ID

Extractpeaklist

ProteinInference

RAW peakspephits prot hits

DetermineCID vs. ETD

TagTrue/Decoyw/ MUSE

Peptide FDRw/ terminus mods


SORCERER Script Example: DTASelect and Census

• Great tools for filtering, reporting and quant from Yates Lab– Available from Yates lab (fields.scripps.edu)

– We recommend it for SILAC etc. (commercial offering in development)

• On SORCERER, install scripts and run census_select.muse– Runs DTASelect, then Census

– View DTASelect report directly from Sorcerer Web GUI

– Runs Census pre-analysis using search results and supplied params/config

census_select.muse -c ~/custom/census/census_config_silac.xml


Hedge Fund IT Model for Proteomics

Server + Software + Storage + Support + Service + Training

Specialized IT PlatformScripting, Visualization

Informaticians

Traders/BiologistsSpecialist End-Users

SORCERER Enterprise Product+Service


Sorcerer product line• Sorcerer 2 — well-established standard

– Self-contained tower (or 2U rack unit)

– Can fit under bench, shared by lab

– One high-end processing node, with integrated storage

– Good match for single Orbi or similar

• Sorcerer Enterprise — new HT platform

– Pre-integrated rack cabinet

– Goes in server room, shared site-wide

– Includes multinode blade server withhigh capacity storage subsystem

– Ideal for multi-instrument throughput


Requirements for PTM Data Analysis

• Robust peptide ID workflow– Heavy-duty compute servers for hedge-fund-class data

crunching

• Scripting platform for prototyping analyses– Generally customized for each workflow

• Both expert “Chef” and “Detective” needed– Semi-custom detective-work is Sage-N’s specialty

For more info, contact [email protected] work with top labs on semi-custom workflow scripting for cancer-related PTMs.

Documents

Insider secrets to PTM analysis using proteomics mass