BIOL 1406

PreLab 6.3

How can I measure the rate of the reaction catalyzed by glucose oxidase?

In lab, you will examine several factors that affect the rate of the chemical reaction catalyzed by glucose oxidase. In this reaction, glucose, water and oxygen are the substrates; while gluconic acid and hydrogen peroxide are the products:

Glucose + ½ O2 + H2O → Gluconic Acid + H2O2


If we want to know how fast this chemical reaction is occurring, we could measure how fast the substrates of the enzyme are used up, or we could measure how fast the products are formed. In your experiments, you will measure how quickly one of the products - hydrogen peroxide (H2O2) - is formed. To enable you do this, 2 compounds have been added to the glucose oxidase enzyme: 4-aminoantipyrine and phenol. When these 2 compounds react with hydrogen peroxide, a pink dye is formed:
 

H2O2 (colorless) + 4-aminoantipyrine + phenol → pink dye


Therefore, the faster hydrogen peroxide is formed, the faster the solution will turn pink.

Your Turn
Explain why the production of hydrogen peroxide (which is colorless) turns the reaction mixture pink:

Hint

Check your answer.


To estimate the rate of the reaction, you could simply eyeball how fast the reaction mixture turns pink. However, this would not be very accurate. A much more accurate way to measure the rate of the reaction involves using a spectrophotometer. A spectrophotometer (the Spec-20 in our lab) measures how much light of a specific wavelength is absorbed by a solution (optical absorbance). It turns out that the wavelength of light most strongly absorbed by the pink dye is 510 nm. As hydrogen peroxide is formed, the concentration of pink dye in the reaction mixture will increase, the pink color will get darker, and the optical absorbance at 510 nm (A510 values) will increase. Therefore, we can measure the rate of the reaction catalyzed by glucose oxidase by measuring how fast the A510 values of the reaction mixture increase. Once you have collected your data, you will analyze the relationship between time and A510 values using linear regression.

 

Your Turn
1. Use Excel, or another spreadsheet program, to make a scatter diagram of the data in Table 6.1 below. If you forgot how to make a scatter diagram with Excel, consult Excel Quiz 3.
 

Table 6.1 A510 values for a mixture of glucose oxidase,
4-aminoantipyrine, phenol, and glucose at selected time intervals
Time elapsed Absorbance at 510 nm
0 sec 0
15 sec. .085
30 sec. .168
45 sec. .256
60 sec. .311
90 sec. .505
2 min. .565
3 min. .602

Note: Absorbance has no units. Also note that the time units in this table are not consistent. When you plot your graph, all time measurements must be listed using the same units (i.e. all in seconds or all in minutes.)
2. Review the Prelab Exercise on Graphing to make sure you have included all necessary information on your scatter diagram.
3. After you have completed your scatter diagram, examine it carefully and try to visualize the smooth line that would most closely match the 8 data points. This line is called an “enzyme progress curve”. The slope of the line at any given point is the rate of the reaction, and is a measure of “enzyme activity”. Notice that this line would have a steeper slope during the early time intervals (up to about 90 seconds), but would gradually “flatten out” as you move further towards the right side of the graph. Can you explain why this curve eventually flattens out over time?

Check your answer.

Actually, this is a fairly typical result when comparing two variables in a biological experiment. Often there is a linear (i.e. straight line) relationship between the variables when the independent variable has low and/or moderate values. But this relationship may “break down” as we approach extremely high (or in some cases extremely low) values of the independent variable, causing the “best fit” curve to “flatten out” (or in some cases to steepen). Therefore, although we could try to fit a straight line to all of the data points on our scatter diagram, we should look for signs that the linear relationship is “breaking down” at the extreme ends of the curve. In our example, because the best-fit line “flattens out” with the last two data points, you should fit a straight line to the first six data points only. It is only in this region where a true linear relationship exists
4. Use Excel to create a second scatter diagram using only the first 6 data points from Table 6.1 above. Then carry out linear regression to determine the best-fit straight line for these six data points. Plot the best-fit straight line (trendline) on your scatter diagram along with correlation coefficient and the linear regression equation. Print your graph. If you forgot how to carry out linear regression with Excel, consult Excel Quiz 3.

5. Your regression analysis will give you the equation for the straight line that best fits your data. The general equation for a straight line can be written as follows:

y = mx + b
(Where m = the slope of the line, and b = the y-intercept)
Linear correlation coefficient for your data Check your answer.
Based on the linear correlation coefficient, should you conclude that time and A510 values were linearly related during the first 90 seconds of the reaction? Explain.

 Check your answer.
Fill in the following values. Be sure to use the correct units of measurement.
Slope; and  y-intercept Check your answer.
Equation for this line Check your answer.
The linear regression equation tells you the exact mathematical relationship between the 2 variables, x and y. Therefore, if you know the value of one variable, you can substitute it into the equation and calculate the corresponding value of the other variable. In addition, the slope of the linear regression line in this case is a measure of the rate of the reaction catalyzed by glucose oxidase.

 


Close this browser window to return to Blackboard and complete the practice quiz and assessment quiz.