Extracting quantitative information from proteomic 2-D gels Lecture in the bioinformatics course ”Gene expression and cell models” April 20, 2005 John Gustafsson Mathematical Statistics Chalmers

Proteomics lectures: starting points Anders’ starting point this Monday: –Let’s say that we want to study life at the protein level – what technologies do we have at hand? Today’s lecture: –How can we get (large-scale) quantitative measurements of protein amounts? So that we can do statistics and bioinformatics

Proteomics The 2-D gel technology Extracting quantitative information –Image analysis of 2-D gels Comparison with microarrays Statistic analysis of quantitative 2-D gel data Content and structure

Proteomics DNA mRNA ProductionModificationDegradation Localisation Interaction ACTIVITY P TDP Co-factors 2-D gels

2-D gel electrophoresis: Protein separation and quantification ”protein soup” spot volume  protein quantity molecular size molecular charge acidicalkaline small large

A typical 2-D gel experiment statistical analysis conclusions protein extracts biological experiment controltreatment 2-D gel images 2-D gel electrophoresis quantified data image analysis matrix with spot volume data rows: proteins (many) columns: gels (few) experimental design Example:

The image analysis task The task 1.In each gel image: Find and quantify the protein spots 2.In the group of gel images: Match protein spots in different images that correspond to the same protein Issues –automation –time

Pseudo-color superposition 1(3) 0M NaCl1M NaCl

Pseudo-color superposition 2(3) OM NaCl1M NaCl

Pseudo-color superposition 3(3) (red: 0M NaCl, blue: 1M NaCl)

The standard solution – workflow In each gel image 1. Background subtraction 2. Spot detection 3. Spot quantification In the group of gel images 4. Spot pattern matching

1. Background subtraction BeforeAfter - =

2. Spot detection / image segmentation

3. Spot quantification spot volume  protein quantity

4. Spot pattern matching

The typical 2-D gel experiment statistical analysis conclusions protein extracts biological experiment controltreatment 2-D gel images 2-D gel electrophoresis quantified data image analysis matrix with spot volume data rows: proteins (many) columns: gels (few) experimental design Example:

Limitations Technological –hydrofobic proteins don’t dissolve –limited pI/size coverage –limited labeling/staining Image analytical –Limited global matching efficiency of automatic algorithms –Need for time consuming manual guidance –”The image analysis bottle-neck”

Limited global matching efficiency Voss and Haberl (2000)

Incomplete spot detection: Faint spots Detected Not detected

Incomplete spot detection: Close spots

Proteomics The 2-D gel technology Extracting quantitative information –Image analysis of 2-D gels Comparison with microarrays Statistic analysis of quantitative 2-D gel data Content and structure – revisited

Comparison with microarrays 2-D gelsMicroarrays Labeling one channel*one or two-color Background subtr. yes Spot detection HARDeasy Spot quantitation can be difficultquite easy Spot matching HARDknown Identification MS or reference atlasknown *) recently also two-color

Variability normal1M NaCl normal1M NaCl biological replications growth condition

Variance versus mean dependence A dot in the plot: –the measurement of one protein The quadratic dependence indicates a multiplicative error structure (2x5 gel set; normal growth condition) slope=2  variance  mean 2

Why transform the data? A mathematical data transformation can be used to –Make errors more normally distributed –Stabilize variance versus mean dependence Then the model on transformed scale is more simple than on original scale Simplifies the subsequent analysis

Logarithmic data transformation Stabilized variance versus mean dependence after a logarithmic data transformation (2x5 gel set; normal growth condition)

Statistical analysis of quantitative 2-D gel data Examples: Test of differential expression Cluster analysis –cluster proteins –cluster cell/tissue samples Classification –classify tissue samples (i.e. tumor classes)

Proteomics The 2-D gel technology Extracting quantitative information –Image analysis of 2-D gels Comparison with microarrays Statistic analysis of quantitative 2-D gel data Summary

An alternative approach to the matching problem The standard solution –First spot detection –Then matching of point patterns An alternative, recent approach –Matching at the pixel level –Computationally heavy

Gel matching at the pixel level Reference image Image warping Original imageAligned image

Future alternatives to quantitative 2-D gels? Quantitative masspectrometry Protein arrays