It has 2D gel electrophoresis and data analysis of 2D gel (image analysis).

1. DATA ANALYSIS OF
2DGEL
SUBMITTED BY:
PRATEEK KUMAR
M.Sc BIO-INFORMATICS

3. INTRODUCTION:
 Gel Electrophoresis is used to separate
proteins from the mixture of different proteins
of different molecular size.
 2D Gel Electrophoresis separates the
proteins of same molecular size.
 It was given by O’Farrell and Klose in 1975.
 Firstly, the Serum proteins were separated
by using this method.
 It separates the proteins based on molecular
size as well as charges.

5. The goal of two-dimensional
electrophoresis is to separate and display
all gene products present.
 It is the only method currently available
which is capable of simultaneously
separating thousands of proteins.
 The two dimensions of 2D PAGE are –
-iso electric point
-size
 Therefore, it has unique capability
to capture detailed info about protein
expression, isoforms, complex formation
and post translational modification.
e.g.- chemotherapy to cancer cells,
occupational benzene exposure to
blood cells.

6. Progress :-
- Chemical or Mass spectrometric
analysis
- Immobilized pH gradient (IPG) gels
- More sensitive detection procedures
- Computer software.
Drawbacks :-
- Poor reproducibility
- Limited sample loading

7. SAMPLE LOADING ON IPG
GELS:
BIO-RAD PROTEAN IEF cellAmersham Pharmacia Biotech
IPGphor
Multiphor II

8. DATA ANALYSIS:
 To study the variations in protein expression among a
series of gels, the gels should be matched together.
 Data analysis can be carried out at two different levels-
 1- Analyze gels- Study protein expression changes within
a set of gels, without taking populations into
consideration.
 The analytical methods used include scatter plots,
descriptive statistics, histograms, and factor analysis.
 2- Analyze Classes- Find significant protein expression
changes between classes of gels. For this type of
analysis, images must be placed in classes and opened
in s classes sheet.
 The analytical methods used include descriptive statistics

9. MAJOR STEPS IN GEL ANALYSIS:
 Data acquisition
 Gel processing / visualization
 Spot detection and quantitation
 Gel matching
 Gel comparison
 Data analysis
 Gel annotation - building a database
 Link to databases (Internet)

10. PROCESS
Preparati
on
• Collect samples for 2DE.
• The sample was spiked with a denatured and
fluorescently prelabelled protein standard( for accurate
alignment of gel images).
Processi
ng
• The standard proteins were selected for their mol size
and charges to ensure a standard image that covers the
gel as much as possible.
Labeling
• The std images and protein sample were electroblotted
from the SDS-PAGE gel to a membrane followed by
immunolabelling and visualization by digital camera
capture.

11. Imaging
• Sample image- chloroluminiscent-
gel signal image
Imaging
• Standard image- flouroscent- gel
standard image
Purpose
of
images
• Signal image -> proteins to be studied
• Standard image -> image alignment

12. STAINING
Sensitive, quantitative and MS-compatible.
 Comassie brilliant blue R250 staining (30-100
ng)
 Colloidal comassie blue G250 staining (30-100
ng)
 Diamine silver stain (1-10 ng) : gluteraldehyde
 Silver nitrate stain (1-10 ng)
 Sypro Ruby fluorescent stain
 Flamingo fluorescent gel stain.

14. IDENTIFICATION OF SPOTS:
 Comparison with a reference gel.
 Extraction of spots and biochemical
analysis.
 The protein is detected as a strip of
interconnected spots with different sizes and
shapes.
 The spots change their shape and size with
stimulation, as well as increase/decrease in
number.

15. 2DE Gel Analysis –what are we looking
for?
 interesting protein spots
-different abundance caused by
variation of experimental factor
 reliable findings
-statistical analysis
-based on replicates
 Perfect basis for quantitative
analysis: complete expression
profiles

16. IN GEL DIGESTION:
 Spot picking (gel excision) – manual or
mechanical ?

17.  image analysis aspects
-speckle artefacts
-varying signal intensity
-background signal
 matching of spots across gels
-differences in spot positions
-differences in spot patterns
-conflicting pair-wise spot matching
 missing spots
-unique spot matching
-statistical significance

18. IMAGING SOFTWARE:
Amersham Pharmacia
Biotech
Typhoon
BIO-RAD
Molecular Imager FX

19. Imaging

20. OTHER SOFTWARES ARE:
 BioNumerics 2D
 Delta 2D
 ImageMaster
 Melanie
 PDQuest
 Progenesis and REDFIN

21. MASTER GEL E.coli:

22. Alignment
 Alignment of the signal images is required to
handle spatial offset between gel images, and is
achieved by manually aligning all images to a
reference image.
 To avoid bias from the protein expression in
alignment, separate standard gel images are
used in the alignment process

23. Normalization
 Normalization of the recorded images is needed
because there will still be some gel to- gel image
variability in 2D gel electrophoresis, mainly due to
manual preparation and handling of membranes.
 The application implements three normalization
schemes:
1. The mean normalization-uses the mean pixel
value in each image as a normalization scale .
2. The median normalization- uses the median pixel
value in each image as the normalization.
3. The Z-score scale normalization- implements a z-
score normalization of each pixel based on the
mean and the standard deviation of each image.

24. RESULT-
After alignment, the user selects an external
variable(e.g. age, height, survival in months) and
runs the correlation analysis. This will result in a
Spearman rank correlation value, a normalized
standard deviation, and a p-value resulting from a
correlation t-test or permutation test for each pixel
column in the gel stack. For each of these types of
values an image is created.
Heat map visualization is used to present
the results.
The correlation measurement was performed
by calculating the Spearman rank correlation
between a chosen external variable (e.g. age, sex,
survival in months) and the set of pixels at each
pixel coordinate (x, y).

25. • the t-test for correlated samples, for the
simple reason that the two sets of
measures in such a situation are arranged
in pairs and are thus potentially correlated.
• it typically involves situations in which each
subject is measured twice, once in condition A,
and then again in condition B.
• it is very effective in removing the extraneous
effects of pre-existing individual differences.
t-test

26. Proteomic databases
 Collection of data obtained by 2D gels analysis.
 It includes:
- Annotated images of 2D gels.
- Description of identified proteins.

27. SWISS-2DPAGE:
 Created in 1993
 Collaboration with Central Laboratory of Clinical
Chemistry, University Hospital of Geneva , Swiss
Institute of Bioinformatics
 36 reference maps
– Plasma (27%), E. coli (18%, 8 maps), Mouse
(17%, 6 maps)
– Human lymphocytes, Staphylococcus aeurus
 1265 protein entries
 4309 identified spots.

28. QUERY INTO THE
DATABASES:
 http://www.expasy.org/ch2d/
 Query by keywords
 Graphical query
 List of identified proteins per master.

29. GRAPHICAL QUERY RESULT:

31. The Spearman rank correlation is a measure
of how a change in the external variable
corresponds to an increase or decrease in
the image pixel intensity.