Avalekander Week 3

From OpenWetWare
Jump to navigationJump to search

Purpose

The purpose of this assignment is to improve students skills in reading a scientific research paper. Additionally, the topic correlates to what is being discussed in class in regards to molecular biology. This paper furthers our learning of the many uses of microarrays in determining gene expression and transcriptional patterns.

Definitions of unfamiliar words

  1. Shine-Dalgarno sequence- A short stretch of nucleotides on a prokaryotic mRNA molecule upstream of the translational start site, that serves to bind to ribosomal RNA and thereby bring the ribosome to the initiation codon on the mRNA (https://www.biology-online.org/dictionary/Shine-dalgarno_sequence).
  2. Biogenesis- The process in which life forms arise from similar life forms (https://www.biology-online.org/dictionary/Biogenesis).
  3. Photomultiplier- An evacuated electronic tube which converts light into a measurable electric current. Light falling on a photocathode releases electrons, which are accelerated by an electric field and attracted to the first dynode (positive electrode), where they liberate more electrons which are attracted to the second dynode, and so on. A common type of photomultiplier in astronomical use has ten dynodes, each at an increasingly positive electric potential. The flow of electrons arriving at the final anode is proportional to the amount of light falling on the photocathode. Photomultipliers are widely used for photometric measurements in astronomy, such as of variable stars (J. Law & R. Rennie, 2015).
  4. Diauxic shift- When yeast cells are grown in liquid cultures, they metabolize glucose predominantly by glycolysis, releasing ethanol in the medium. When glucose becomes limiting, the cells enter diauxic shift characterized by decreased growth rate and by switching metabolism from glycolysis to aerobic utilization of ethanol (L. Galdieri, S. Mehrotra, S. Yu, and A. Vancura, 2010).
  5. Dendrogram- a branching diagram representing a hierarchy of categories based on degree of similarity or number of shared characteristics especially in biological taxonomy. (https://www.merriam-webster.com/dictionary/dendrogram).
  6. Protein kinase A signalling pathway- Protein kinase A (PKA) signaling is a widely used intracellular pathway and the major route for channeling the second messenger cAMP signal. Ligand activated G-protein coupled receptors that transduce the signal via the Gs alpha subunit of the heterotrimeric G protein lead to activation of the adenylyl cyclase enzymes (AC) that catalyze the formation of cAMP from ATP. (https://rgd.mcw.edu/rgdweb/pathway/pathwayRecord.html?acc_id=PW:0000543&species=Rat).
  7. Hierarchial clustering- Hierarchical clustering, also known as hierarchical cluster analysis, is an algorithm that groups similar objects into groups called clusters. The endpoint is a set of clusters, where each cluster is distinct from each other cluster, and the objects within each cluster are broadly similar to each other. (https://www.displayr.com/what-is-hierarchical-clustering/)
  8. Trehalose metabolism- Trehalose is a non-reducing disaccharide formed by two glucose molecules. It is widely distributed in Nature and has been isolated from certain species of bacteria, fungi, invertebrates and plants, which are capable of surviving in a dehydrated state for months or years and subsequently being revived after a few hours of being in contact with water. This disaccharide has many biotechnological applications, as its physicochemical properties allow it to be used to preserve foods, enzymes, vaccines, cells etc., in a dehydrated state at room temperature (G. Iturriaga, R. Suárez, and B. Nova-Franco, 2009).
  9. Menadione- Menadione or 2-methyl-1,4-naphthoquinone is a vitamin K analog, which can undergo one-electron reduction by enzymes including microsomal NADPH–cytochrome P450 reductase and mitochondrial NADH–ubiquinone oxidoreductase (complex I), resulting in redox cycling, or it can undergo detoxification via two-electron reduction by NAD(P)H–quinone oxidoreductase (Luderer U., 2014).
  10. Dithiothreitol (DTT)- Dithiothreitol (DTT, 0.5–5 mM) has sometimes been included in the assay buffer to inhibit either ligand or receptor degradation. At 0.1–0.5 mM, DTT can markedly increase binding by reducing ligand degradation (McQueeen and Semple, 1991).

"Cold Adaptions in Budding Yeast" Outline

Introduction

  1. What is the main result presented in this paper?
    • Expression patterns and transcriptional responses vary depending on the length of time cells are shocked by the cold. The late cold response was similar to the more general early stress response with similar genes induced or repressed, however, the early cold response and the early stress response did not show much overlap in genes expressed signifying that there must be unique regulation of early cold response in yeast. The ECR involves induction of genes in RNA metabolism and lipid metabolism, as well as increased fluidity of the cell membrane, whereas genes induced during the LCR mostly encode proteins that protect the cell against a variety of stresses.
  2. What were the limitations in previous studies that led them to perform this work?
    • Little is known about the mechanisms responsible for the growth and survival of organisms at low temperatures and this motivated the researchers to conduct the study
      • Physical and biochemical changes in the cell due to cold temperatures
        • Membrane fluidity is decreased
          • Slower lateral diffusion
          • Activity of membrane-associated enzymes is decreased
          • Reduced membrane transport
        • Stabilized mRNA secondary structures in prokaryotes
    • Goal of the paper is to describe the transcriptional response of yeast when subjected to cold-shock in both wild type strains and mutant Δmsn2Δmsn4 cells. Also, the cold-shock responses are compared with the response of yeast to other environmental stressors.

Methods

  1. How did they treat the yeast cells (what experiment were they doing?)
    • Wild type yeast cells were analyzed every 10 minutes, 30 minutes, or 60 hours, as well as at the 0,2, or 12 hour point.
  2. What strain(s) of yeast did they use? Were the strain(s) haploid or diploid?
    • The strains of S. cerevisiae used were BY4743 and BSY25. For the growth curve experiments W303 cells were used. The cells were all diploid.
  3. What media did they grow them in? What temperature? What type of incubator? For how long?
    • The cells were grown in YPD medium (2% glucose, 2% bactopeptone, and 1% yeast extract). Incubated in a 10 degree celsius water bath shaker during which temperatures decreased 4 degrees celsius per minute. Yeast cells were harvested during their log phase at either 30 degrees celsius (control) or 10 degrees celsius (experimental).
  4. What controls did they use?
    • The controls were kept in 30 degree celsius temperatures.
  5. How many replicates did they perform per treatment or timepoint?
    • At 10 minutes, 30 minutes, or 60 hours there were three replicates
    • At 0,2, and 12 hours there were two replicates.
  6. What method did they use to prepare the RNA, label it and hybridize it to the microarray?
    • Three micrograms of mRNA were labeled by incorporating Cy3- and Cy5-dCTP through reverse transcription
    • Resulting cDNA was hybridized onto yeast genomic microarrays
    • Prehybridization was done in 20:1:1 DigEasyHyb solution, yeast tRNA and salmon sperm for 2 hours at 42 degrees celsius
    • Microarrays were washed twice in buffer at 42 degrees celsius, airstream dried and then hybridized.

Results & Discussion

  1. What mathematical/statistical method did they use to analyze the data?
    • DNA spots had to pass three quality control tests
      • Signal intensity had to be significantly greater than the intensity of the background
      • Signal intensity must be within the dynamic range of the photomultiplier tub
      • Raw intensities for duplicate spots had to be within 50% of each other
      • Statistical analysis and visualization, as well as hierarchal clustering, were performed with GeneSpring software.
  2. Are the data publicly available for download? From which web site?

Figures

  • Figure 1a: Two-dimensional hierarchical cluster analysis of microarray data
    • x-axis: Distinguishes between LCR or ECR gene that is either down regulated (green) or up regulated (red)
    • y-axis: Time that cells were exposed to a cold environment
    • Measurements: Measurements were made using microarray data and clustering was done through the GeneSpring software.
    • Conclusions: Statistically significant variation was found of at least twofold on some of the 634 genes analyzed. A, B, and C letters represent the ECR genes and D and E represent the LCR genes. The letter F was also included but it was never explained as to what F represented.
  • Figure 1b: Classification of ECR genes
    • x-axis: Represents cell functions
    • y-axis: Represents the number of genes involved in the ECR
    • Measurements: Data was categorized based on MIPS classification and the SGD database
    • Conclusions: The genes that regulate the cold response transcribe different genes with different functions depending on the length of time exposed to the cold.
  • Figure 1c: Classification of LCR genes
    • x- axis: Represents cell functions
    • y-axis: Represents the number of genes involved in the LCR
    • Measurements: Data was categorized based on MIPS classification and the SGD database
    • Conclusions: The genes that regulate the cold response transcribe different genes with different functions depending on the length of time exposed to the cold
  • Figure 2: Transcriptional profiles of early cold response during temperature downshifts
    • x-axis:Time that cells are exposed to cold shock
    • y-axis: Red:Green ratio during transcription (induced=red;repressed=green)
    • Measurements: Ratios of red:green found through the use of microarrays compared with the microarray data of Gasch et al., 2000
    • Conclusions: Some of the resulting clusters from this study in comparison to the previous study done by Gasch are consistent but other expression patterns appear different in the two experiments.
  • Figure 3a/b/c: Transcriptional responses of ECR genes compared to LCR genes and their comparisons to the ESR
    • x-axis: Time period of stressor and distinction between types of stress tested
    • y-axis: Red:green ratio to depict level of gene expression
    • Measurements: Compared with the Cold shock data by using GeneSpring (standard correlation).
    • Conclusions: ECR genes show a reciprocal transcriptional response when compared with other ESR but the LCR is similar to the ESR in terms of genes expressed
  • Figure 4: Regulation of gene expression during cold treatment. The cold-responsive genes were clustered based on wild type expression patterns and the mutant strains during ECR (2 h) and LCR (12 h).
    • x-axis: Time and the strain- either the wild type or mutant
    • y-axis: Red:Green ratio during transcription
    • Measurements:Gene expression ratios averaged from duplicate or triplicate experiments for the following times and temps- 0hr (30C), 2hr (10C), and 12hr (10C).
    • Conclusions: There was less change in transcription in the mutants compared with the wild type
  • Figure 5: Accumulation of glycogen and trehalose in the wild type as well as mutant strains during cold shock
    • x-axis: Time that mutant or wild type spent in cold environment
    • y-axis: Glycogen or trehalose present in cells
    • Measurements: The levels of glycogen and trehalose were measured at various times after undergoing a temperature shift from 30 to 10°C. The results are an average of three independent experiments.
    • Conclusions: Wild types showed an increase in glycogen as well as trehalose storage after more time had passed and particularly after the 12th hour of cold. Glycogen storage was greater than trehalose but storage rates for the wild type strains were much greater than those with mutated genes signifying the important role of the gene for nutrient storage.
  • Figure 6: Comparison of results obtained in this study with that of Sahara et al. (2002) in regard to transcriptional response to cold
    • x-axis: Time passed and distinction between data obtained in this study versus Sahara et al's study
    • y-axis: Red green ratios of microarray data
    • Measurements: Measurements were made using the microarray data and clustered (using GeneSpring) and comparing it with the results of Sahara et al. (2002).
    • Conclusions: The ECR ribosomal gene data found by Sahara contradicted the results found in this study. However, the both found similar results based on the LCR and the general stress response.

Conclusions

  1. How does this work compare with previous studies?
    • The results of previous studies including that of Sahara, Homma, and Jones and Inouye reported opposing data for some of the findings. For instance, Sahara et al. (2002) described the induction of ribosomal genes during short cold treatments, whereas Schade et al. observed a decrease in transcript abundance for ribosomal genes. There was similar findings in regards to the LCR and ESR genes but different findings for the ECR gene. Jones and Inouye also found a repression of heat shock proteins during cold shock. Sahara and this paper found common clusters of genes.
  2. What are the important implications of this work?
    • Yeast is a simple, unicellular model organism that has similar cellular organization to other eukaryotic organisms making it an ideal and easy to study organism. Gene regulation and expression in yeast cells in response to cold-shock could lead to other findings that could help humans in the future.
  3. What future directions should the authors take?
    • The authors of this experiment should definitely look into the regulatory factors that allow yeast to survive in cold temperatures as they suggested. Additionally, maybe they should get in contact with the authors of the similar experiments who reported different findings for similar tests to determine why the results varied.
  4. Give a critical evaluation of how well you think the authors supported their conclusions with the data they showed. Are there any major flaws to the paper?
    • I definitely did not think that there were any major flaws to the paper but there were a few minor areas that could have been made more clear. For instance, in figure 1a there is a letter F included in the figure but it was never explained. The letters A-E were discussed and it was made clear what they represented but there was no mention of what letter F signified. I think it would have also been beneficial to include some of the statistical analysis that was done to really prove the significance behind what was found.

Acknowledgements

  • I would like to acknowledge my homework partner, Alison with whom I texted a few times and also worked with to present the figures 4 & 5.
  • Additionally, Desiree and I also texted a few times about the assignment.
  • I referenced the directions for this assignment found on the week 3 assignment page BIOL388/S19:Week 3

Except for what is noted above, this individual journal entry was completed by me and not copied from another source. Avalekander (talk) 19:50, 6 February 2019 (PST)

References

Links

Retrieved from "https://openwetware.org/mediawiki/index.php?title=Avalekander_Week_3&oldid=1059417"