Sea Urchin VE Removal…Prediction of Molecular Weights of unknown By:Michael Dinse Elizabeth...

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 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 0.9974

Special Cubic

SSError 0.0029

DegFreedom 3.0000

StdDeviation 0.0313


R-square 0.9932

Special Log

SSError 0.0014

DegFreedom 3.0000

StdDeviation 0.0214


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 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 0.866505591 0.97852453 0.9991073 0.999225

Special Cubic

SSError 0.0002

DegFreedom 2.0000

StdDeviation 0.0095


R-square 0.9992

Special Log

SSError 0.0008

DegFreedom 2.0000

StdDeviation 0.0205


R-square 0.9965

Special Cubic

SSError 0.0001

DegFreedom 2.0000

StdDeviation 0.0074


R-square 0.9995

Special Log

SSError 0.0008

DegFreedom 2.0000

StdDeviation 0.0205


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.

Sea Urchin VE Removal…Prediction of Molecular Weights of unknown By:Michael Dinse Elizabeth...

Documents

Transcript of Sea Urchin VE Removal…Prediction of Molecular Weights of unknown By:Michael Dinse Elizabeth...