sea urchin ve removal…prediction of molecular weights of unknown
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Sea Urchin VE Removal…Prediction of Molecular Weights of unknown. By:Michael Dinse Elizabeth Gutierrez Maria Uribe. Purpose. - PowerPoint PPT PresentationTRANSCRIPT
Sea Urchin VE Removal…Prediction of Molecular Weights
of unknown
By:Michael Dinse
Elizabeth Gutierrez
Maria Uribe
Purpose
• Observe Vitelline envelope peptides that have been isolated by two chemical methods (alpha-amylase & DTT) and a mechanical isolation (manual) and predict their molecular weights through a process of analysis, measurments, and various calculations.
Method/Process• Data Collection
– Measure four different gels, each containing seven different bands (1 standard, 2 alpha-amylase, 2 DTT, and 2 manuals)
• Model the standards using the following methods – linear, linear (Using Log MW), quadratic,
cubic, special cubic, and special log.
• Determine which one is the best model in order to predict our unknown data set.
Tools
• Measurements of Gel bands were made using images from Photoshop.
• Calculation and Analysis of the data was completed using Excel and Minitab.
Description of the Vitelline Envelope, AA, and DTT
• Before we proceed it is important to give a brief description of the Vitelline Envelope and the two chemical methods (alpha-amylase & DTT).
The Vitelline Envelope
• Composed essentially of proteins, the vitelline envelope acts as the protective layer just above the egg’s inner membrane.
• In sea urchins this protective layer is in the egg’s jelly.
Fertilization of a Sea Urchin
http://www.mhhe.com/biosci/cellmicro/kalthoff/sample_ch04.pdf
Alpha-amylase
• “Alpha-amylase (1,4-alpha-glucan 4-glucanahydrolase; Ec 3.2.1.1) are ubiquitous enzymes which catalyze the breakdown of amylose and amylopectin through the hydrolysis of internal alpha-1,4-glycosidic linkages with net retention of anomeric configuration.”– http://www.yorvic.york.ac.uk/projects/2/2.2.3.htm
Alpha-Amylase
• Alpha-amylase are found “in a diverse array of industrial processes..[including]..the pharmaceutical industry.” – http://www.yorvic.york.ac.uk/projects/2/2.2.3.htm
DTT (Dithiothreitol)
• “Dithiothreitol (DTT) is commonly used in biochemical research to protect sulfhydryl groups from oxidation or reduce disulfide linkages to free sulfhydryl groups in proteins and enzymes.”– http://www.wcaslab.com/tech/Dithiothreitol.htm
Data Collection
• Measured four different gels using Photoshop– Gel #1: 12%: Method Comparison– Gel #2: replicate of Gel #1– Gel #3: 10%: Method Comparison– Gel #4: replicate of Gel #3
Data Collection
• Each gel that was measured contained seven different bands– 1 Standard – 2 Alpha-Amylase (AA)– 2 Dithiothreitol (DTT)– 2 Manual
• Each band was measured three times in order to obtain a more accurate reading.
Models Analyzed
• Using the standard bands the following models were analyzed: – linear/linear(Using Log MW)….y=mx+b– quadratic……………….....y=a+bx+cx^2– cubic……………………...y=a+bx+cx^2+dx^3– special cubic……………...y=a+bx+cx^3– special log………………. y=a+bx+clnx
Model/Analysis
• For each of the five different models, predicted values, standard deviations, and the R-squared was calculated.
Best Model
• After analyzing the r-squared and the difference between the confidence intervals, the best fit model was chosen.
Best Model
• These are our results for the best model….– Gel #1: 12%……………………...CUBIC– Gel #2: replicate of Gel #1……….CUBIC– Gel #3: 10%……………….SPECIAL CUBIC– Gel #4: replicate of Gel #3...SPECIAL CUBIC
Why did the Cubic Model best predict the data set for Gel #1 and Gel #2?
• GEL #1
• GEL #2
Linear Linear(Log MW) Quadratic Cubic
SSError 4527054380 0.024364732 0.0007235 0.000155
DegFreedom 4 4 3 2
StdDeviation 33641.69429 0.078046031 0.0155294 0.0088
R-square adjusted 0.700185418 0.929026997 0.99719 0.999098
R-square 0.76014716 0.943253789 0.9982193 0.999608
Linear Linear (Log MW) Quadratic Cubic
SSError 4611129918 0.025174251 0.0011676 0.000229
DegFreedom 4 4 3 2
StdDeviation 33952.65055 0.079331979 0.0197281 0.010696
R-square adjusted 0.694617322 0.926668915 0.9954652 0.998667
R-square 0.755696061 0.941273504 0.9973309 0.999367
Special Cubic
SSError 0.0020
DegFreedom 3.0000
StdDeviation 0.0259
R-square adjusted 0.9922
R-square 0.9953
Special Log
SSError 0.0011
DegFreedom 3.0000
StdDeviation 0.0191
R-square adjusted 0.9957
R-square 0.9974
Special Cubic
SSError 0.0029
DegFreedom 3.0000
StdDeviation 0.0313
R-square adjusted 0.9886
R-square 0.9932
Special Log
SSError 0.0014
DegFreedom 3.0000
StdDeviation 0.0214
R-square adjusted 0.9947
R-square 0.9968
Why did the Special Cubic Model best predict the data set for Gel #3 and Gel #4?
• GEL #3
• GEL #4
Linear Linear (log MW) Quadratic Cubic
SSError 1957732034 0.005471912 0.0001471 0.000102
DegFreedom 3 3 2 1
StdDeviation 25545.5934 0.04270797 0.0085772 0.010123
R-square adjusted 0.81764907 0.969793684 0.9987817 0.998303
R-square 0.86323935 0.977336222 0.9993201 0.999682
Linear Linear (Log MW) Quadratic Cubic
SSError 1910929577 0.005170857 0.0002236 0.000178
DegFreedom 3 3 2 1
StdDeviation 25238.39388 0.041516492 0.0105729 0.013329
R-square adjusted 0.82200844 0.971455581 0.9981488 0.997058
R-square 0.866505591 0.97852453 0.9991073 0.999225
Special Cubic
SSError 0.0002
DegFreedom 2.0000
StdDeviation 0.0095
R-square adjusted 0.9985
R-square 0.9992
Special Log
SSError 0.0008
DegFreedom 2.0000
StdDeviation 0.0205
R-square adjusted 0.9930
R-square 0.9965
Special Cubic
SSError 0.0001
DegFreedom 2.0000
StdDeviation 0.0074
R-square adjusted 0.9991
R-square 0.9995
Special Log
SSError 0.0008
DegFreedom 2.0000
StdDeviation 0.0205
R-square adjusted 0.9930
R-square 0.9965
Analysis of unknowns
• Once a best model was determined predicted values for the six lanes of unknowns were computed using the equations for the best fit models.
• In order to convert these values to molecular weights the antilog of the predicted values was taken.
Analysis Continued...
• Once Molecular weights were known averages of the two lanes of AA, DTT, and manual were taken.
• Using the manual column as our reference the averages for AA and DTT were compared.
Molecular Weight (Band) Comparison
GEL 1ALPHA DTT MANUAL SUM OF DIFF.
241726199754.8
164467 178922.1 167684.8 14455.17429119802.1 130313.3 10511.18208
106952.2 99484.17 104596.1 7468.001778871.48 81027.74 2156.2537
72446.15 73650.63 71911.6 2273.57714767260.1562908.4 64672.93 3971.07953255901.36 59872.44 558.8115861
53483.06 53014.5 53573.31 50752.5196750752.52 49359.65 1837.125001
45723.57 47643.9 45806.78 3882.77235941557.76 43546.05 40610.52 38452.81271
37252.6 37852.7 33731.2039933731.2
31599.09 32382.77 31945.78 29986.3049529986.3 29966.75 28712.52989
28712.5327252.6
GEL 2ALPHA DTT MANUAL SUM OF DIFF.
197342.8168107.9
139890 142541 141123.9 2651.039006117782.8 113147.3 4635.48993798758.99
94290.18 91016.67 93519.94 3273.51294185386.4 75207.42 10178.97937
66772.55 68823.07 67564.92 2050.518660884.06 60596.18 287.879645657211.9 56143.02 1068.87305253841.68
50682.34 51655.66 50362.32 1613.36806149776.3647831.69 47518.67 313.0144477
44394.97 45798.09 45480.01 1403.11447141310.86 42106.8 41614.69 795.9440551
36840.28 38458.98 1618.69938234182.06
33623.14 34058.54 435.408971431424.38 32086.5 32364.11 1217.34512729918.8 29774.82 30025.81 358.0153482
28452.2126976.46
Molecular Weight (Band) Comparison Continued...
GEL 3Alpha DTT Manual SUM OF DIFF.126429.9 132075.6 130510.8 5645.73344187343.42 93919.17 89724.34 6575.74942776853.35 83952.9 74622.16 11561.9285
70511.6662347.06 66325.76 65101.37 3978.705932
59364.28 58332.02 1032.26125454923.23 54268.51 654.7163378
49733.4148812.06 48516.38 48438.9 450.652128844984.77 45614.34 45468.84 629.5645393
43331.63 43089.33 242.298591942848.6 42250.53 42147.93 803.275559741864.17 41874.9 10.72885074
41954.7942412.35
43538.33 43552.23 13.89998003
GEL 4Alpha DTT Manual SUM OF DIFF.124753.2675 129238.7711 126510.7053 4485.50360787279.0531 92402.2547 88012.1567 5123.20156778215.0493 82789.6446 73567.2327 13870.22856
70180.891162246.5901 65417.8012 64292.9544 3171.211104
58352.2807 58800.0124 447.731728154989.7677 53922.0933 1067.67439151659.5435 49758.8476 1900.695841
48874.2693 48503.2119 48098.8013 1179.87863547123.7447 46815.4049 308.3397288
44467.4965 45514.2630 45230.6015 1046.76652842810.4946 43211.0168 42930.2984 400.5222127
42257.5477 42048.1921 209.355607141865.687741983.780742544.3060
43681.7605 43491.5617 43710.7282 248.1341075
Conclusions
• From the analysis it can be demonstrated that in the case of the 12% gels the method which gave results similar to those which were obtained manually was that of AA.
• The reasoning behind this conclusion is due to the fact that extra bands were obtained in DTT which did not exist in the manual obtained unknowns.
Conclusions
• From the analysis it can be demonstrated that in the case of the 10% gels the method which gave results similar to those which were obtained manually was that of DTT.
• The reasoning behind this conclusion is due to the fact that DTT obtained more bands in common with the manual than AA.
Conclusions
• In the 10% gel, one standard band was lost.
• In the 10% gel, each lane lost the lower band (which went to the die front).
• In the 10% gel, the bands were not as dense as in the 12% gel.