Yeast+Signaling+Session+3+Post-lab+Assignment+-+F22 3

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Yeast Signaling Session 3 Post-lab Assignment (Individual) (15 points) Introduction (2 point): 1. A paragraph with a biological rationale for why you did this experiment, your research hypothesis and your null hypothesis. The biological rationale is your reasoning that explains why you think your experiment is logical and your hypothesis is true. Your rationale combines what you know about the system and what you learn from the literature or internet searches. Literature should be cited as in the examples at the end of this assignment! The hypothesis leads directly from your rationale, providing a clear prediction of the outcome of your experiment. Your research hypotheses should include methods, predictions and spell out the independent variables to be compared, the dependent variables that will be measured, the direction of the outcome, and the system that you will be working with. Your research hypothesis should address how you predict your treatment will affect alpha factor-mediated signaling. You should either have two separate hypotheses with predictions, one addressing the treatment’s effect on mating gene transcription activity and a second regarding cell shape, or one hypothesis with predictions that addresses both mating gene transcription and cell shape. Refer to your lab instructor’s comments from Session 2’s in-lab assignment for this section. In this experiment, we decided to use the 3S mutant peptide, as it has a serine (S) at position 3 instead of tryptophan (W) at position 3, which is in the wild-type alpha factor. Tryptophan is a nonpolar amino acid, and its side chain is aromatic. Serine, on the other hand, is a polar amino acid, and its side chain is significantly smaller [than that of tryptophan] and only consists of 5 elements (CH 2 OH). Due to the difference in the amino acid sequence, the 3S mutant strand will most likely stimulate a lesser response compared to the unmutated alpha factor ligand. Serine is not capable of the same interactions that tryptophan is. For example, tryptophan is capable of π-π interactions (Vitale et al, 2017). The first four amino acids in the alpha factor are primarily involved in signaling (Naider and Becker, 2004). As a result, in order to properly recognize the alpha factor, the Ste2 receptor [of the alpha factor] has likely evolved so that its sequence is perfectly complementary to the sequence in the wild-type alpha factor. Due to the mismatch in the receptor-ligand interactions and considering that Serine is not capable of the same interactions that Tryptophan is, the 3S mutant alpha factor will likely be unable to properly bind to the Ste2 receptor, which will likely lead to a lesser response when compared to the unmutated alpha factor ligand. In addition, it has been noted that scrambled mating pheromone peptides fail to adopt the proper structures (Vitale et al, 2017). Based on this reasoning, it is possible that the presence of serine instead of tryptophan will cause our alpha factor to take on a different structure than the wild-type peptide, which will contribute to the lack of proper

ligand-Ste2 receptor interactions. This will also prompt a lesser response, leading to less transcription of the FUS1 gene (Robinson et al., 2020). Based on this rationale, which supports the notion that the response of the yeast “a” cell to the 3S mutant alpha factor compared to the yeast’s response to the wild-type alpha factor will be different, we developed the research hypotheses: When we examine the shapes of the cells exposed to the 3S mutant alpha factor in the cell-shape assay, the amount of shmooing cells will be lower compared to the cells exposed to the wild-type alpha factor. Similarly, the Miller Unit reading obtained through the beta-galactosidase assay for the cells exposed to the 3S mutant alpha factor will be lower compared to the cells exposed to the wild-type factor. For these hypotheses, we implement two systems: the cell shape assay and the beta-galactosidase assay. The independent variable in our experiment is the type of alpha factor we use: the 3S mutant alpha factor and the natural, unmutated alpha factor. More specifically, the variable that we are implementing is the presence of serine at position 3 in the 3S mutant alpha factor, while the natural, unmutated alpha factor has a tryptophan at position 3. The dependent variables are shmooing within cells (cell shape assay) and the Miller Unit reading (beta-galactosidase assay). The null hypothesis for our experiment is: If we use the 3S mutant alpha factor instead of the wild-type alpha factor, there will be no difference in the cell shapes observed in the cell-shape assay (the amount of shmooing cells will be the same), and the Miller Unit reading obtained through the beta-galactosidase assay for cells exposed to the mutant and nonmutant alpha factors will be the same. Results (6 points): You will be graphing both your own group’s data, as well as the pooled class data posted to the Canvas site for this section. For the pooled class data, only use the spreadsheet that corresponds with the specific alpha factor mutant that your group used. A description of bar graphs can be found on pages A-7 and A-8 of the Statistics Appendix. Calculation of the standard error of the mean (SEM) is found on pages A-3 to A-5. 2. (1.5 points) From your own group’s data: A bar graph showing the effect of your alpha factor mutant compared to your controls on mating gene transcription as measured by beta-galactosidase activity expressed as Miller units . You should average your replicates so that you have one bar on this graph representing each treatment condition (untreated, alpha factor-treated and mutant alpha factor-treated).

3. (1.5 points) From your own group’s data: A bar graph showing the effect of your alpha factor mutant compared to your controls on cell shape. This graph should have a total of 9 bars if each cell shape was observed for each condition. For each cell shape (unbudded, budded or shmoos), there should be three bars representing the three conditions, untreated, alpha factor and mutant alpha factor. These 3 bars representing the different conditions should be 3 different colors. The height of the bar should indicate the percentage of a particular cell shape under that condition. You should average your replicates so that you have one bar on this graph representing each cell shape for each treatment condition (untreated, alpha factor-treated and mutant alpha factor-treated).

4. (1.5 points) From the pooled class data: A bar graph showing effect of your alpha factor mutant compared to the controls on mating gene transcription as measured by beta-galactosidase activity expressed as Miller units. This graph should have 3 bars total, representing untreated cells, alpha factor-treated cells and mutant alpha-factor treated cells. For each condition, the height of the bar should indicate the average beta-galactosidase activity and the error bars should represent the standard error of the mean (SEM). 5. (1.5 points) From the pooled class data: A bar graph showing the effect of your alpha factor mutant on cell shape. This graph should have a total of 9 bars if each cell shape was observed for each condition. For each cell shape (unbudded, budded or shmoos), there should be three bars representing the three conditions, untreated, alpha factor and mutant alpha factor. These 3 bars representing the different conditions should be 3 different colors. The height of the bar should indicate the percentage of a particular cell shape under that condition, and the error bars should represent the standard error of the mean (SEM).

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