Results
In order to determine the number of yeast cells in our culture, and therefore the amount of RNA that could possibly be isolated, the optical density (O.D.) of the cultures was taken at 600 nm. By measuring the O.D. it is possible to determine the growth phase and, therefore, the number of cells contained in the culture (Fig.1). After RNA isolation, the absorbance of the samples at 260nm was measured. By using Eq. 1, it is possible to determine the RNA concentration in the samples and therefore how much sample should be used in the microarray. The RNA purity of our samples was found using a ratio of the sample absorbance taken at 260nm to the absorbance at 280nm. To further analyze the isolated RNA and check for degradation, the RNA was run on a 1.2% agarose gel (Fig. 3).
| Growth Phase | OD 600 | cells/ml |
| early log-phase | < 0.4 | < 10E7 |
| mid log-phase | 0.4 - 1.7 | 1-5 x 10E7 |
| late log-phase | 1.7 -6.6 | 5 x10E7 - 2 x 10E8 |
| stationary phase | > 6.6 | 2 x 10E8 |
Figure 1. The relationship of O.D. reading to number of cells per ml in the culture.
|
O.D. reading x ((40/1000µg/µl)/1 O.D. unit) x dilution factor =
concentration (µg/µl) |
Equation 1. Formula used to determine RNA concentration.
| Phenotype | O.D. Reading | O.D. Reading | Cells/ml | Absorbance | Absorbance | RNA Conc. | RNA Purity |
| at 600nm | x dilution factor | at 260nm | at 280nm | (µg/µl) | |||
| Wild Type | 0.995 | 1.9 | 5x10^7 | 0.061 | 0.026 | 0.244 | 2.3 |
| ZMS2 Mutant | 0.817 | 1.6 | 4x10^7 | 0.139 | 0.076 | 0.556 | 1.8 |
Figure 2. Number of cells, RNA concentration and RNA purity. Ideally, cells should be harvested when the O.D. is between 1.5 and 2.5. Our samples were relatively low compared to this. In addition, the samples should contain a very similar number of cells to be sure the microarray will produce accurate results. A ratio of 1.9 - 2.2 indicates a pure sample, which makes our sample not completely pure.
Figure 3. Gel Electrophoresis of RNA. The first lane (far left) contains the mutant phenotype RNA and the second lane contains the wild type phenotype RNA.
Microarray Analysis
The next portion of the experiment was the analysis of the microarray slides. The slides produced were in poor quality. Because of this, a slide (#106) from an experiment completed in the Fall of 2004 was used (Fig. 4). Gridding and addressing was accomplished using Magic Tool, in order to locate all spots and compare red vs. green pixels.
Figure 4. One section of the chip with gridding. Red and green image files were merged. Red corresponds to the microarray for the yeast with mutated ZMS1 and ZMS2 genes. Green corresponds to the microarray for the wildtype yeast.
Another slide (#107) was merged with ours to compare gene expression. Eighteen genes involved in the oxidative stress response were selected to be analyzed. The ratio of their expression in each slide is shown below (Fig. 5). The ratios of expression were converted to a log2 scale, so positive numbers indicate that the mutant expression (red) was higher, and negative numbers indicate that the wild type expression (green) was higher.
| Gene name | Slide 107 red:green ratio | Slide 106 red:green ratio |
| ZWF1/YNL241C | -0.975752454 | -6.14974712 |
| YHR183W | -0.709409872 | 4.392317423 |
| YIL070C | -0.911772817 | -2.599912842 |
| YJR127C | -0.765014012 | 4.209453366 |
| YNL167C | -0.574470127 | 4.459431619 |
| YGR209C | -0.573374526 | 0.40053793 |
| YBL064C | -2.310998535 | 1.874469118 |
| YKR042W | -0.723419062 | 1.020037753 |
| YPL188W | -0.961816806 | -1.827819025 |
| YDR353W | -1.204571144 | 0.216811389 |
| YGR097W | 0.878693704 | 2.798041171 |
| YER174C | -0.646363045 | -1.715023041 |
| YJL121C | 1.748461233 | -0.409520494 |
| YDL166C | 0.741364058 | 1.447458977 |
| YHR106W | -1.628031223 | -3.636624621 |
| YPL188W | -0.961816806 | -1.827819025 |
| YML007W | 1.033166864 | 2.459431619 |
| "ZMS1"/YJR127C | -0.765014012 | 4.209453366 |
| "ZMS2"/YMR030W | -0.62058641 | -1.454031631 |
Figure 5. Expression ratios for 18 oxidative response genes. In slide107, many of the genes were under expressed, but not by much. Others showed a small amount of over expression. Many more genes were over expressed in slide 106, some even over expressed by as much as 4 and 6 fold. The genes that were under expressed also showed a greater level of under expression (up to 6 fold) than in slide 107.
Graphs of those genes that were upregulated were created. Figure 6 shows a graph of all the genes from the two merged slides that were upregulated by a significant amount. From this graph, the six genes that were underexpressed in both slides were selected and graphed in Figure 7. The table underneath gives the name and function of each of the six genes.
Figure 6. Graph of the genes that were upregulated in each of the two slides. The vertical line on the right shows the expression levels for the genes on our slide (106) and the line on the right shows the expression levels for the other slide (107).
Figure 7. The six genes from Figure 6 that were underexpressed in both slides were graphed by themselves.
| Gene | Common Name | expression | Function |
| YBR180W | DTR1 | Essential for spore wall synthesis | |
| YDR481C | PHO8 | Repressible alkaline phosphatase | |
| YEL020W-A | TIM9 | Mitochondrial intermembrane space protein | |
| YKL048C | ELM1 | Serine/threonine protein kinase that regulates cellular morphogenesis, septin behavior, and cytokinesis; required for the regulation of other kinases | |
| YKL204W | EAP1 | eIF4E-associated protein, binds eIF4E and inhibits cap-dependent translation, also functions independently of eIF4E to maintain genetic stability; plays a role in cell growth, implicated in the TOR signaling cascade | |
| YLR214W | FRE1 | Ferric reductase and cupric reductase, reduces siderophore-bound iron and oxidized copper prior to uptake by transporters; expression induced by low copper and iron levels |
Figure 8. Table with the name and function of each of the six genes from Figure 7.
All genes were grouped together using hierarchical clustering (Fig. 9). This clumps genes together based on similar expression patterns, which were determined by calculating the dissimilarity with the Pearson Correlation Coefficient. The functions of these genes can be seen in Fig.10.
Figure 9. Hierarchical Clustering of genes. Genes that are the farthest to the right are the most similar.
| Gene | Function |
| YGL202W (ARO8) | negative regulator of early meiotic genes |
| YGL028C (SCW11) | cell cycle-regulator gene |
| YBR010W (HHT1) | encodes a histone protein (H3) |
| YCL059C (KRR1) | encodes nucleolar protein required for the synthesis of 18S rRNA and for the assembly of 40S ribosomal subunit |
| YOR027W (STI1) | encodes a heat shock protein |
| YDR459C (PFA5) | encodes for Palmitoyltransferase |
| YPR179C (HDA3) | encodes a subunit of a possibly tetrameric histone deacetylase complex |
| YOL165C (AAD15) | unknown function |
| YNL046W | unknown function |
| YMR301C (ATM1) | mitochondrial inner membrane transporter involved in the maturation of iron-sulfur cluster-containing proteins |
| YAL027W | unknown function |
Figure 10. Table of the eleven most similar genes from the cluster analysis (Fig. 9). The gene name and function is given for each of the eleven. None of these genes particularly correlate to one another so it is unclear as to whether the results are due to the up and down regulation of the gene as caused by the mutation or if the data is completely inaccurate.