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: |
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. | |||||||||||||||||||||
|
|||||||||||||||||||||
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? | |||||||||||||||||||||
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 |
|||||||||||||||||||||
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.