e This means, it is the best.
An example of how the introduction of gaps improves alignments is seen below:
Query AGCAC Score = 2 matches + 2 mismatches = 2 x (+1) + 2 x (-2) = -2
After introducing a gap
Query AGCAC Score = 4 matches + gap = 4 x (+1) + 1 x (-3) = -1
The alignment with the gap is a better match between the two sequences. BLAST divides the sequence of interest to words. Once the highest scoring arrangements are found the alignment is extended to find the best overall alignment. To account for similarity between sequences that takes place at random the Expected value or E-value is introduced. The E-value is a parameter that describes the number of random hits with a particular word size. Essentially the E-value represents the background noise (significance threshold) of an alignment. The closer the E-value is to zero the better is the alignment.
Secondary structure prediction of nucleic acids is straightforward, because secondary structure formation in nucleic acids follows the simple rule of Watson- Crick base pairing: A pairs with T or U using two H-bonds whereas G pairs with C using three H-bonds, thus G-C pairs are more stable than A-T pairs. Among the potential secondary structures the one with the lowest free energy is the most likely structure. The most popular algorithm to predict RNA structure is Mfold, where M stands for multiple, meaning that it generates more than one potential structure and fold stands for structure.
2.6 Identifying Conserved Sequence Elements (Invariable Blocks)
First you will use the sequence of the sensor from the model organism Bacillus subtilis to find toxin sensor sequences in different organisms. Then, you will compare the sequences of the toxin sensor in these different organisms using multiple sequence alignment to identify blocks in the sequence that did not change throughout evolution. Once you have identified the invariable blocks of the toxin sensor, you will choose one that you subject to mutagenesis. You will delete or insert nucleotides into the invariable block of your choosing, or modify its sequence.
2.7 Identifying Conserved Structural Elements
Besides invariable blocks, conserved structural elements may also serve as hot spots for recognition. These are regions in the molecule that may have different sequence, but form the same structure. For example, both the GGGG AAAA CCCC and the AAAA GGGG TTTT nucleic acids form a hairpin even though they have very different sequence. To identify conserved structural elements in the ykkCD toxin sensor first you will predict the secondary structure of the ykkCD sensor RNA using ykkCD sequences from different organisms. Then you will select structural elements that are present in each organism based on visual inspection of the predicted structures. To test if a conserved structural element is important for toxin recognition, you will design a mutant that significantly alters a conserved element, then design another mutant that restores the original structure (compensatory mutation). If the structural element was important for toxin recognition then significantly changing the structure would destroy recognition, but restoring the original structure, albeit with altered sequence, will restore the ability of the sensor to recognize its target toxin.
Identifying invariable blocks
- Go to http://blast.ncbi.nlm.nih.gov/Blast.cgi.
- Click nucleotide blast.
- Paste the sequence below into the “Enter Query Sequence” window.
T G TA A AG T T T T C TAG G G T T C C G C AT G T C A AT T G AC AT G G AC
T G G T C C G AG AG A A A AC A C ATAC G C G TA A ATAG A AG C G C G T
- Choose “others” under “Choose Search Set/Database” and “Somewhat similar
sequences” under “Program Selection”.
- Hit BLAST.
You will see many sequences color-coded by the degree of similarity to the B. subtilis ykkCD RNA.
Find ykkCD sequences in the organisms below and paste them into your lab notebook!
Bacillus subtilis, Bacillus amyloliquefaciens, Bacillus licheniformis, Bacillus halodurans, Bacillus pumilus, Alkaliphilus oremlandii, Staphylococcus saprophyticus subsp