2.1 Learning Objectives
During this lab, you will use bioinformatics to learn how to find the DNA sequence of a given macromolecule and use this sequence to uncover evolutionary sequence conservation. You will use these data to identify conserved sequence segments (invariable blocks) in the ykkCD sensor RNA. During the second half of the lab you will identify conserved structural elements within the toxin sensor. These are elements where the sequence may have been altered during evolution, but the structure was retained. You will then use this information to design a mutant to see if a conserved sequence or structure is important for toxin recognition.
2.2 Mini Project Flowchart
The bolded blocks in the flowchart below highlight the role of the current experiment in the mini project.
2.3 Why is Sequence Conservation Important for Macromolecule Function, and How Do We Determine This?
As you learned earlier, the goal of the mini-project is to better understand the molecular basis of how the ykkCD sensor RNA recognizes the antibiotic tetracycline. You will determine which part of the sensor is essential for tetracycline recognition. The first step toward this goal is to identify segments of the toxin sensor (ykkCD riboswitch) that did not change throughout evolution. We call these segments invariable blocks. These elements are the most likely to play substantial roles in tetracycline recognition. You will subject these elements to site-directed mutagenesis and evaluate how these mutations affect tetracycline recognition by the sensor. Site-directed mutagenesis simply means that you will alter the sequence of the sensor in the bacterial DNA. If the mutation abolishes the ability of the sensor to recognize tetracycline, then the mutated part of the sensor is essential for tetracycline recognition (Fig. 2.1). You will conclude this if the KD (dissociation constant) value of a mutant sensor RNA – tetracycline complex is at least 10-fold larger (recall larger KD value means weaker binding) than that of the wild-type sensor tetracycline complex. If the KD value of the mutant sensor is within an order of magnitude of that of the wild-type sensor tetracycline complex you will conclude that the nucleotides altered were not essential for recognizing tetracycline.
Figure 2.1: Evaluation of ykkCD sensor RNA mutants using binding affinity assays: If >10 (higher KD value) the nucleotide(s) mutated were important for tetracycline recognition. If <10 (low KD value) the nucleotides mutated were not important for tetracycline recognition.
2.4 Review of Nucleic Acid Properties
Before we identify conserved sequence elements and design mutants let us review a few things about nucleic acids. Nucleic acids are macromolecules that contain a chain of nucleotides connected by covalent bonds (phosphodiester bonds). Most nucleic acids contain all four nucleotides: adenine (A), thymine (T) or uracil (U), cytosine (C) and guanine (G). Our toxin sensor is an RNA molecule therefore it contains uracil instead of thymine, but since we perform our mutagenesis in the bacterial DNA we will see T instead of U in the sequence. The sequence of the nucleic acid is determined by the order in which the nucleobases follow each other in the macromolecule, and it determines the properties of the nucleic acid. For example even though the following two nucleic acids, ATCG and GTCA, contain the same bases, since the bases follow each other in different order, the properties of these two nucleic acids will be very different. Secondary structure, the interaction pattern between nucleobases, of a nucleic acid is easily predictable since an A always pairs with a T or a U using two hydrogen bonds and a C always pairs with a G using three hydrogen bonds. These pairs are referred to as Watson-Crick pairs or base pairs. Nucleic acid sequence comparisons and structure predictions are important applications of bioinformatics.
2.5 What is Bioinformatics?
During the last 15 years one of the greatest breakthroughs in biochemistry was the emergence of bioinformatics. Bioinformatics use