A Model to Determine Molecular Weights of Proteins from Gel Electrophoresis

A Model to Determine Molecular Weights of Proteins from Gel

Electrophoresis

By Jose Ceja

Kamyar GhodsCSUN/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

Mol

ecul

ar W

eigh

t (D

)

Male7.5%-L6Male7.5%-L5Female7.5%-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

Mol

ecul

ar W

eigh

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

Mol

ecul

ar W

eigh

ts (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

Mol

ecul

ar W

eigh

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