2.5 Enzymes

Experimental design—accurate, quantitative measurements in enzyme experiments require replicates to ensure reliability. (3.2)
This links to Practical 3 – Experimental investigation of a factor affecting enzyme activity.

Working with enzymes is something that all biology students get very familiar with over their studies!  This is particular true in the new syllabus as Practical 3 requires an enzyme experiment and they are popular as topics for the IA.

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Testing the effect of substrate concentration on potato catalase.

Although there are several other practical-themed NOS statements, this one makes particular reference to the idea of reliability and replicates.  In terms of assessment this is most likely to appear in the Section A of Paper 3, when students are provided with experimental scenarios and have to apply their knowledge. However, it is also important for the IA.  The chosen investigation must design a methodology that will collect sufficient data, the data must be processed with appropriate awareness of uncertainties, and the reliability of the results reviewed and evaluated in the conclusion and evaluation.

This is thus an important lesson to not just experience the practical side of biology, but to understand the importance of replicates and how this impacts the IA.  So what could this look like? Here are a few ideas:

  • If an enzyme-based experiment, aim for five variations of the independent variable (five different pHs; five different temperatures etc). As enzyme experiments are invariably time-based, this will allow you to plot a graph with more confidence (five data points rather than, say, three).
  • Try to repeat each variation five times.  This will provide enough data to calculate the average and standard deviation. Of course there are more processing options than this (think rate of reaction) but these two are the basics.
  • The conclusion/evaluation needs to then assess how the range of the independent variable, the sample size and the processed data contribute to the reliability of the experiment. The more replicates you have, the more robust this section will be.
  • There are always time constraints on how many replicates you can collect – so factor this into your methods.  If your experiment is only collecting data for three minutes for each run, then you should be able to get more replicates (and you will be expected to collect more data).  If, in contrast, you are collecting data for more than an hour per experiment, then you will need to be aware of this.
  • Finally, remember that design, processing and evaluation are all relative to the specific experiment you carried out – so always think in terms of the context for your investigation and the resources available to you.

 

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