Post on 20-May-2015
description
Subject trainingon
Computational Tools for Animal Genome Resource Data Analysis
Dec 02-13, 2013
DiGE
Dr Karan Veer SinghScientist
National Bureau of Animal Genetic ResourcesKarnal
2-D gel electrophoresis
2D analysis experiments commonly address questions like Protein level Differences caused by
disease state drug treatment life-cycle stage
Some protein level differences studied are small and the results are affected by experimental variation originating both from the system and from inherent
biological variation
Misdiagnosis is dangerous
Limitations of conventional 2D gel
6 gels made from the very same sample, run in parallel (SYPRO Ruby)
Conventional 2-D
control gel 1
treated gel 2
Are spot differences real?
Differences??
1. Only one dye can be used at a time for one gel
2. We run as many gel as many samples are there
3. Cannot control the variation in loss of proteins for each gel
4. Differential analysis is difficult
5. Statistical confidence is less6. Proteins with PI beyond the pH limits of strips cannot be
focused on strips
Variation in 2D gel
System related variations
1. Gel-to-gel variation, which can result from differences in electrophoretic conditions between first dimension strips or second dimension gels, gel distortions, sample application variation and user-to-user variation.
2. Variation due to user-specific editing and interpretation when using the data analysis software.
Inherent biological variation
Inherent biological variation arises from intrinsic differences that occur within a population. For example, differences from animal-to-animal, plant-to-plant or culture-to-culture which have been subjected to identical conditions
Induced biological change
1. Differences due to disease state, drug treatment, life cycle stage
Least gel to gel variation
Normalization of biological variation
Least number of gels run
Differential expression analysis
Statistical confidence in presenting our result
How to avoid uncontrolled protein loss
Is there any way out
What we want ???
Covalent derivatization of proteins with fluorophores in complex protein mixturesprior to IEF and SDS-PAGE allows detection and quantification of differences in protein
abundance between different biological samples within one single gel
DIGE system allows the inherent biological variation to be effectively differentiated from induced biological changes
DIGE system is capable of detecting and quantifying differences as small as 10% between samples (above system variation) with greater than 95% statistical confidence.
What is DIGE and why is it needed
Unique dyes Experimental
design
DeCyder software
CyDye™ DIGE Fluor minimal dyesDyes chemistryUniqueness
The internal standardRandomization
Identification of spotsCodetection of spotsSpot volume ratioNormalizationStats t test and ANOVA
DIfference Gel Electrophoresis
CyDye DIGE Fluor minimal dyesChemical description
1. Spectrally distinct: resolvable dyes (Cy™2, Cy3 and Cy5), discrete signals
2. Size and charge matched: labeled samples co-migrate within gel
3. Each adds 450 Da to the mass of the protein. This mass shift does not effect the pattern visible on a second dimension SDS PAGE gel.
4. multiplexing possible: A protein labeled with any of the CyDye DIGE Fluor minimal dyes will migrate to the same position on the second dimension SDS PAGE gel
5. Photo stable: minimal loss of signal
6. pH insensitive: no change in signal over wide pH
SensitivityGreat sensitivity: down to 25 pg of a single protein, and a linear response to protein concentration up to five orders of magnitude (105).
*silver stain detects 1–60 ng of protein with a dynamic range of less than two orders of magnitude*Comassie Brilliant Blue sensitivity = 0.5µg/cm2 of protein present in a gel matrix
Fluorophore
Excitation peak (nm)
Emission peak (nm)
Cy2 488 520 (yellow)
Cy3 532 580 (Blue)
Cy5 633 670 (Red)
Protein labeling Minimal labeling: With CyDye DIGE Fluor minimal dyes 50 μg protein is labeled in each reaction with 400 pmole dyes. The ratio ensures that the dyes label approximately 1–2% of lysine residues so each labeled protein carries only one dye label and is vizualised as a single protein spot.
The lysine amino acid in proteins carries an intrinsic +1 charge at neutral or acidic pH. CyDye DIGE Fluor minimal dyes also carry a +1 charge which, when coupled to the lysine, replaces the lysine’s +1 charge with its own, ensuring that the pI of the protein does not significantly alter.
Experimental design
1. Inclusion of an internal standard sample on each gel
2. The requirement for biological replicates such as multiple cultures, tissue etc.
3. Randomization of samples to produce unbiased results, thus conforming with best experimental practice
4. No gel replicates of the same sample is needed
RandomizationConditional bias
Are we applying specific dyes to specific sample inadvertentlyBiological replicates (sampling bias)
Good experimental practice
Randomize - within each groupLabel half of each group with Cy™3 and half
with Cy5
Randomization of samples
Randomization of samples across gels removes any bias from the experiments such as experimental conditions, sample handling and labeling
Even if the system related result variation is low using DIGE System it is good laboratory practice to distribute individual experimental samples evenly between different CyDye DIGE Fluor dyes and different gels to avoid systematic errors.
A1 A2 A3 A4
B1 B2 B3 B4
C1 C2 C3 C4
Using internal standard
Benefits of the internal standard
Gel-to-gel (system) variation is eliminated
The internal standard appears on all gels and contains all spots (average)
Easier gel-to-gel matching (between identical spot maps)
2-D DIGE is the only protein 2-D approach which allows multiplexing
2-D DIGE is the only 2-D approach enabling use of an internal standard
DeCyder™ 2-D Differential Analysis Software is designed to work with an internal standard
The internal standard is used to match and normalize the protein patterns across different gels thereby negating the problem of inter-gel variation, a common problem in standard “one sample per gel” 2D electrophoresis experiments
The internal standard allows accurate quantization of differences between samples
Internal standard
Advantages of using an internal standard
Accurate quantification and accurate spot statistics between gels
Increased confidence in matching between gels
Flexibility of statistical analysis depending on the relationship between samples
Separation of induced biological change from system variation and inherent biological variation
Are spot difference
real
Experimental design 2D DIGEExperimental design 1 color 2 D
1-color 2-DNo automation (complex)SlowPoor accuracy 24 gels, labor intensive
DeCyder™ Differential AnalysisAnalysis automatedRapid data analysisHigh accuracy for Quantification /trend mapping12 gelsAnalysis fast and highly automated
A comparison between classical 2-D and 2-D DIGE
How to use internal standard
DIGE offers
AccuracyBetter interpretation of results
Reduces the impact of uncontrolled gel to gel variationReduces the number of gels
DeCyder 2D
To compare protein spot volumes across a range of experimental samples and gels, two distinct steps are required
• Intra-gel co-detection of sample and internal standard protein spots• Inter-gel matching of internal standard samples across all gels within theexperiment
Co-detects image pairsRemoves background
Removes dust particlesNormalises images
Matches up to 500 image pairst-test and ANOVA calculated for each spot
Data displayed as Trend analysis graphlow user interaction,
high throughput and low experimental variation
Intra gel co-detection
Inter-gel matchingIt is important to ensure that the same protein spots are compared between gels.
Master image Spot map species
Protein abundance/Differential expressionDirect comparison of spot volume or compare the ratio of spot volume of sample to
the internal standard???
Differences in spot intensity that may arise due to experimental factors during the process of 2D electrophoresis, such as protein loss during sample transfer, will be the same for each sample within a single gel, including the internal standard.
Statistical tests of protein abundance in DeCyder 2D
Student’s T-test and ANOVA. The statistical tests compare the average ratio and variation within each group to the average ratio and variation in the other groups to see if any change between the groups is significant.
Extended Data Analysis (EDA) module of DeCyder 2D
Multivariate statistical analyses such as Principal Component Analysis (PCA), Pattern AnalysisDiscriminant Analysis
Image analysisDeCyder 2D with or without EDAImageMaster 2D Platinum
These dedicated 2D software products use the internal standard to minimize gel to-gel result variation. A detection of less than 10% difference between samples can be made with more than 95% statistical confidence
Six modules in DeCyder1. Image Loader2. Batch Processor3. DIA (Differential In-gel Analysis): background subtraction, in-gel normalization and gel artifact
removal.4. BVA (Biological Variation Analysis): Matching of multiple images from different gels to provide
statistical data on differential protein abundance levels between multiple groups5. XML Toolbox: Extraction of user specific data from XML files generated in either the Batch, DIA or
BVA modules. This data can be saved in either text or html format enabling users to access data from DeCyder 2D workspaces in other applications
6. EDA (Extended Data Analysis): Multivariate analysis of data from several BVA workspaces. EDA is an add-on module for the DeCyder 2D software and can handle up to 1000 spot maps
Principal Component AnalysisPattern analysisDiscriminant analysisInterpretation
Image loadingNaming gel imagesGel 01 Standard Cy2.gel,Gel 01 (Time1_Dose2) Cy3.gelGel 01 (Time2_Dose2) Cy5.gel
Differential In-Gel Analysis (DIA)- performs spot co-detection (up to 10,000)-spot quantification by normalization and ratio calculation-Contrast adjustment (~65000 vs 256 grey scale)
Biological Variation Analysis (BVA)- processes multiple gel images- performs gel to gel matching of spots- allowing quantitative comparisons of protein expression across multiple gels
Analytical experiments design
DIGE summary
3 different CyDye DIGE fluors are available
Complete system approach from sample preparation to MS ID
Sample multiplexing - up to 3 samples on each gel
Fluorescence detection with wide dynamic range
Automated high throughput image analysis platform
Statistics associated with results