Bacterial Transformation: Antibiotic Selection and Positive & Negative Controls

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  • 0:08 Bacterial…
  • 0:45 Bacterial Colonies
  • 3:01 Experimental Control
  • 4:27 Positive Control
  • 5:11 Negative Control
  • 6:15 Significance of…
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Lesson Transcript
Instructor: Greg Chin
The use of antibiotic selection and positive and negative controls are important elements of interpreting data from a bacterial transformation. In this lesson, you will learn how antibiotic selection results in colony formation and how controls help pinpoint the cause of experimental problems.

Review of Bacterial Transformation and Genetic Engineering

We have been considering the steps necessary to produce genetically engineered bacteria capable of producing human insulin. First, we inserted the human insulin gene into a bacterial plasmid using restriction enzymes and ligase. Then, we inserted this recombinant plasmid into the bacteria E. coli using a transformation protocol that featured calcium chloride and heat shock. But, what exactly would successful experimental results look like?

Bacterial Colonies

The kanamycin resistance gene in the plasmid makes it resistant to the kanamycin antibiotic.
Antibiotic Resistance Gene

Recall that even though we're taking steps to increase the probability that a transformation event will occur, bacterial transformation remains a relatively infrequent event. To distinguish the few transformed cells from the millions of untransformed ones, we use antibiotic selection. Since the plasmid housing the human insulin gene also contains an antibiotic resistance gene, say the kanamycin resistance gene, bacteria carrying our recombinant insulin plasmid will be resistant to the antibiotic kanamycin.

Bacterial colonies in a petri dish
Bacterial Colonies

E. coli cells that were not transformed with the recombinant plasmid will be killed by this antibiotic. The handful of cells that remain will grow into bacterial colonies. A bacterial colony is an aggregate of bacterial cells that grew from a single progenitor cell. Consider for a moment what the plate would look like if we could see all the microscopic E. coli cells on the plate immediately following our transformation protocol.

Although there are thousands or millions of E. coli on the plate, most are going to be killed by the antibiotic in the plate. The remaining recombinant cells will undergo many rounds of cell division. As more and more copies of the original recombinant cell are added, a colony that is visible to the naked eye is formed.

It is important to note that each colony consists of clones of the starting recombinant cell. That is, barring a rare spontaneous mutation event, the cells of each colony should be identical. Since spontaneous mutation is relatively rare under experimental conditions, every cell in a bacterial colony is usually identical. This means that any biological product produced by these clones will be identical as well. This is particularly important both to a researcher who wishes to limit variables affecting his or her experiment and to a pharmaceutical manufacturer who wishes to guarantee patients that the medicine provided is safe.

Experimental Control

When conducting an experiment, it's always important to consider all the possible outcomes.

It would be fantastic if every transformation experiment always worked perfectly, but unfortunately we live in an imperfect world, so we should probably be prepared in case we get less-than-perfect results. Previously, we learned that a control is a means of ensuring that only one factor is being tested at a time. Typically, this involves setting up two groups to compare: the experimental group, which has been altered by a single variable, and the control group, which remains unchanged.

For instance, say I want to test new fertilizer. If I didn't include a control group (that is, plants that were not treated with the experimental fertilizer), I would have no way of knowing if the fertilizer only appeared to work poorly. If the seeds were too old or the soil was too dry, we might incorrectly conclude that the new fertilizer doesn't work. By comparing the growth of the experimental group to an untreated control group, we'd notice that neither group of plants grew and draw a completely different conclusion than we might have without the control.

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