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Lecture 6Comparative analysis

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General workflow for proteomic analysis

SampleSample preparation

Protein mixture Sample separation and visualisation

Comparative analysis

DigestionPeptides

Mass spectrometry

MS dataDatabase search

Protein identification

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Data analysis

Sequence of events for comparative analysis

Scanning of image

Image processing

Spot Detection

Gel Matching

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Scanning of imageConvert ‘analog’ spots on gel into digital data

High resolution images on densitometers/imaging systems

For wet or dried gels that have been stained, X-ray films and blots

(Biorad, Biosurplus.com, Institute of Arctic Biology)Oct 2011 SDMBT

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(Proteomic Identification of 14-3-3ζ as an Adapter for IGF-1 and Akt/GSK-3β Signaling and Survival of Renal Mesangial Cells, Singh et al., Int J Biol Sci 2007; 3:27-39 )

Densitometry

(UIC)

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Densitometry

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Image Processing

Digital data converted into Gaussian curves.

Algorithms used to smoothen curve, removing statistical noise

Contrast enhancement to see better spots

Background subtraction to remove meaningless changes in the background of the gel

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Smoothing Gaussian curves

(BARS,Statlib)

Raw data

curve #1

curve #2

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Contrast enhancement

(brneurosci.org)

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Background subtraction

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Image Processing

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Contrast enhancement

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Smoothing

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Background subtraction

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Spot detectionAutomatic detection aided by manual input

Need to adjust sensitivity

Too little sensitivity = missed spots

Too much sensitivity = false positives

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Spot detection

Overlapping spots

Streaks

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Gel Matching

(Proteomics – from protein sequence to function, Pennington & Dunn [editors])

Compare identical spots on different gels

Matching is seldom 100% due to variations in experimental techniques (staining, gel preparation)

Use of landmarks to improve matching

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Gel Matching

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Manual spot matching Matched

Unmatched

(Biorad)

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(Proteomics – from protein sequence to function, Pennington & Dunn [editors])

Data AnalysisAfter matching, data are arranged into a table

Subjected to normalisation to account for inconsistencies in staining and gel preparation

Normalise by:

•Total gel intensity

•Total intensity of subset of spots

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Data Analysis

(Biorad)

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e.g. with CyDye (GE Bioscience)

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Internal standard to make sure that abundance is normalised and variationIs due to biological variation rather than gel-to-gel variation

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Lecture 7In-gel digestion

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General workflow for proteomic analysis

SampleSample preparation

Protein mixture Sample separation and visualisation

Comparative analysis

DigestionPeptides

Mass spectrometry

MS dataDatabase search

Protein identification

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Rationale for digestion of proteins

Error is proportional to mass of the protein

PTMs further complicate assignments based on mass

Sensitivity of MS measurement increases with the use of smaller peptides (6-20 amino acids)

Proteases are able to cut at specific amino acid residues

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Trypsin

(ExPasy PeptideCutter)

Arginine or Lysine Proline

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Chymotrypsin

(ExPasy PeptideCutter)

Tryptophan, Tyrosine and Phenylalanine (major)

Proline

Leucine, Methionine and Histidine (minor)

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Peptide masses from tryptic digest

(Mass Spectrometric Sequencing of Proteins from Silver-Stained Polyacrylamide Gels, Shevchenko et al., Anal. Chem. 1996, 68, 850-858)

Peptide Cutter

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Typical protocol for in-gel digestion

•Excision of Commassie stained spot(s) from gel(s)

•Destaining with NH4HCO3 /acetonitrile

•Reduction with DTT

•Alkylation with IAA

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Overview of in-gel digestion

•Absorption of minimal amount of trypsin into gel (on ice)

•Overnight incubation of trypsin at 37ºC

•Extraction of peptides from gel with 5% formic acid in NH4HCO3 /acetonitrile, or trifluoroacetic acid

•Clean up by ZipTips (removes ionic salts)