a model to determine molecular weights of proteins from gel electrophoresis by jose ceja kamyar...
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A Model to Determine Molecular Weights of Proteins from Gel
Electrophoresis
By
Jose Ceja
Kamyar Ghods
CSUN/JPL-PAIR 2001
Outline
• Getting the data (Standards)
• Choosing a Model
• Getting the data (Unknowns)
• Applying the model
• Results and conclusions
Getting the Data
• Two Methods were used:
• Adobe Photoshop• Spot Viewer
Choosing a Model• Cubic of form:
log(MW)=a+b(RM)^2+c(RM)^3
• Cubic of form: log(MW)=a+b(log(RM))^2+c(log(RM))^3
• Quad Cross Validation of form: log(MW)=a+b(RM)+c(RM)^2
• SLIC
R-squared values
R^2 cubic R^2 logvslog R^2 quadratic SLIC R^20.998474201 0.996826989 0.998101144 0.8199653310.998374109 0.996438939 0.997927349 0.7838732820.997613398 0.995592952 0.998122027 0.8417257050.999277693 0.998768666 0.961205471 0.8583994780.999349397 0.998984631 0.99926587 0.8987178420.999532322 0.998752274 0.999007192 0.8970733290.999156965 0.998995702 0.99913475 0.7834753110.999683346 0.999667791 0.952916318 0.8445056860.999350391 0.999374277 0.993653215 0.8272862130.999704933 0.999575949 0.994743706 0.858422394
Cross Validation
Cubic Cross Validation Quadratic Cross ValidationAverage Bias STD Average Bias STD
5.10 0.20 0.004341 b/w 5.07 0.23 0.0041534.92 0.14 0.010027 w/b 4.98 0.09 0.0107124.85 0.14 0.005736 w/b 4.90 0.09 0.0079034.76 0.07 0.011781 w/w 4.77 0.05 0.0075564.58 0.07 0.006705 b/b 4.57 0.08 0.0079434.38 0.11 0.008265 b/b 4.34 0.15 0.0092694.13 0.20 0.014715 b/w 4.10 0.23 0.0133613.89 0.27 0.011892 w/b 3.98 0.18 0.0129244.08 0.27 0.013554 b/b 4.13 0.32 0.017821
Applying Our Model
• Collected unknown data using Photoshop
• Spot viewer not designed for 1D gels and not well understood.
• Applied best cubic model to each gel.
Applying Our Model
• Created an average of our two data sets
• Applied cubic model to all
• Each standard had 3 cubic fits
• Used data that had the best cubic fit for each standard
Jose's cubic Avg. cubic Komy's cubic
0.998474201 0.998479979 0.9982377470.998374109 0.998422789 0.9982176190.997613398 0.998058698 0.9982155580.999277693 0.998947849 0.9983946360.999349397 0.999502212 0.9995572480.999532322 0.999666967 0.9997305770.999156965 0.999388038 0.9995138540.999683346 0.999498821 0.9991899230.999350391 0.999090399 0.9987093490.999704933 0.999573455 0.999354771
Jose’s Unknown
• Frog skin Gels @ 7 and 12% for males and females
• Within the same gel different lanes had different bands.
• Male and Female frog’s skin do not have the exact same proteins
7% Male & Female frog skin
0
50000
100000
150000
200000
250000
0 0.2 0.4 0.6 0.8 1 1.2
Relative Mobility
Mo
lec
ula
r W
eig
ht
(D)
Male7.5%-L6
Male7.5%-L5
Female7.5%-6
Male and Female Frog Skin @ 12%
0
50000
100000
150000
200000
250000
300000
350000
0 0.2 0.4 0.6 0.8 1 1.2
Relative Mobility
Mo
lecu
lar
Wei
gh
t (D
)
"Male @ 12%"""
Female @ 12 %
Komy’s Unknown
• Comparing 3 methods• Overall the Manual
method found the most proteins and the Amylase method found the least.
• The replicates of each gel were pickkin up more and different proteins.
Molecualr Weights vs Relative Mobility
0
50000
100000
150000
200000
250000
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Relative Mobility
Mo
lec
ula
r W
eig
hts
(D
)
Amylase
DTT
Molecualr Weights vs Relative Mobility
0
50000
100000
150000
200000
250000
300000
350000
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Relative Mobility
Mo
lecu
lar
Wei
gh
ts (
D)
Amylase
DTT
Conclusions & Future Work
• We both found that the higher concentrations found more proteins.
• Photoshop is more reliable for dense 1D gels.
• Out of the four models we tried, the cubic model was the best one.
• Further study is needed to find a true function relating RM to MW.
Aknowledgements
• We thank CSUN/JPL-PAIR program, especially Dr. Carrol, Dr. Clevenson, Dr. Shubin, V. Hutchins and J. Handy.
• And our fellow students
Cubic Residuals Quad Residuals0.00 0.00 0.00 0.01 0.13 0.11 0.14 0.120.01 0.01 0.01 0.02 0.02 0.02 0.02 0.040.01 0.02 0.02 0.01 0.03 0.03 0.03 0.010.01 0.01 0.01 0.00 0.05 0.05 0.06 0.060.00 0.00 0.00 0.01 0.24 0.23 0.25 0.02
0.00 0.080.00 0.23
Residuals