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Sea Urchin VE Removal…Prediction of Molecular Weights of unknown

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

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Sea Urchin VE Removal…Prediction of Molecular Weights of unknown

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

  2. 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.

  3. 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.

  4. Tools • Measurements of Gel bands were made using images from Photoshop. • Calculation and Analysis of the data was completed using Excel and Minitab.

  5. 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).

  6. 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.

  7. Fertilization of a Sea Urchin http://www.mhhe.com/biosci/cellmicro/kalthoff/sample_ch04.pdf

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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.

  13. 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

  14. Model/Analysis • For each of the five different models, predicted values, standard deviations, and the R-squared was calculated.

  15. Best Model • After analyzing the r-squared and the difference between the confidence intervals, the best fit model was chosen.

  16. 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

  17. Why did the Cubic Model best predict the data set for Gel #1 and Gel #2? • GEL #1 • GEL #2

  18. Why did the Special Cubic Model best predict the data set for Gel #3 and Gel #4? • GEL #3 • GEL #4

  19. 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.

  20. 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.

  21. Molecular Weight (Band) Comparison

  22. Molecular Weight (Band) Comparison Continued...

  23. 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.

  24. 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.

  25. 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.

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