Matthew K. Oki Individual Journal 14

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Week 14 Individual Journals

Part 1 In-Class Assignment

  1. What database did you access? (link to the home page of the database)
  2. What is the purpose of the database?
    • "Provides for the first time detailed information on genes and associated genetic variants involved in digenic diseases, the simplest form of oligogenic inheritance."
    • http://dida.ibsquare.be/
  3. What biological information does it contain?
    • This database contains information on chromosome mutations. It shows the original allele, alternative allele, what kind of mutation it is, and what disease this is correlated with.
    • http://dida.ibsquare.be/browse/#
  4. What species are covered in the database?
  5. What biological questions can it be used to answer?
    • This database can be used to look into what types of mutations cause certain diseases. This database pools together certain diseases and relates that to what kind of mutation each one is exhibiting.
    • http://dida.ibsquare.be/statistics/
  6. What type (or types) of database is it (sequence, structure model organism, or specialty [what?]; primary or “meta”; curated electronically, manually [in-house], manually [community])?
    • Since anyone can submit data to this database, it is a primary database that is curated manually (in-house). "New submissions will only be accepted after careful manual inspection."
    • http://dida.ibsquare.be/submit/
  7. What individual or organization maintains the database?
  8. What is their funding source(s)?
  9. Is there a license agreement or any restrictions on access to the database?
  10. How often is the database updated? When was the last update?
    • There is no clear information given on how often the database is updated. However, it does have a yearly count of how many publications there were. This graph stops at 2015.
    • http://dida.ibsquare.be/references/
  11. Are there links to other databases?
  12. Can the information be downloaded? And in what file formats?
  13. Evaluate the “user-friendliness” of the database.
    • The website is well designed and organized.
    • The website informs the reader/user about what the database is about on the home page. It gives background on digenic diseases. There is also a help header that gives information on how to work finding and submitting data.
    • In order to run a specific query, you really need the name of the disease you are looking for information on. You can also sort data by which kind of mutation it is.

Part 2 Group Project

Biological Terms

  1. Sinusoidal: "Varying according to the regular undulating sine curve y = sin x."
  2. Diurnal: "Happening daily, or during the course of a day."
  3. Kinetics: "The study of the rates of chemical reactions or biological processes."
  4. Mesophilic: "describing organisms, especially bacteria, that grow best at temperatures of about 25–45°C."
  5. Succinate: "A salt of succinic (butanedioic) acid, HOOC(CH2)2COOH, a four-carbon fatty acid. Succinate occurs in living organisms as an intermediate in metabolism, especially in the Krebs cycle."
  6. Chemostat: "An apparatus in which a bacterial population can be maintained in the exponential phase of growth by regulating the input of a rate-limiting nutrient and the removal of exhausted medium and cells."
  7. bioreactors: "Reaction vessels used to grow large numbers of cells that synthesize a product of interest. Originally developed for fermentation to produce antibiotics but more recently used to grow large numbers of selected or genetically engineered cells (e.g. for production of monoclonal antibodies or recombinant proteins)."
  8. budding index: "a method of release of virus from a cell after replication has taken place: viral protein associates itself with an area of cell membrane, which forms a coat or envelope around the virus; some cellular proteins in the area of budding are replaced by virus-coded proteins"
  9. argon laser: "a type of laser that utilizes argon gas to produce a beam of intense light, used especially in eye surgery to treat disease of the retina" (e.g. diabetic retinopathy) or glaucoma (as in argon laser trabeculoplasty)
  10. Metabolites: "A product of metabolism, including intermediate and waste products, or something which takes part in the reactions"
  11. transcriptome: "The full complement of all types of RNA molecules in a cell. The study of the transcriptome gives insight into the real-time activity of an organism at the molecular level."
  12. Off-gas: "a gas that is given off, especially one emitted as the byproduct of a chemical process."
  13. Biogenesis: "The principle that a living organism can arise only from another living organism, a principle contrasting with concepts such as that of the spontaneous generation of living from non-living matter"
  14. Vacuolar protein: "any of numerous proteins that are involved in the vesicle‐mediated transfer of enzymes to the yeast vacuole. Many share similarity with proteins from higher eukaryotes."
  15. Concomitant: "at the same time: describing drugs that are administered together or symptoms that occur during the same period"
  16. Flow Cytometry: "the technique for counting or measuring some property of cells, or subcellular components, using a flow cytometer, often after labelling with a fluorescent marker"
  17. Upregulation: "An increase in the sensitivity of a cell to a chemical substance, such as a hormone, signal molecule, or drug, due to an increase in the density of cell-surface receptors for that molecule. The converse, downregulation, reduces the cell’s sensitivity"
  18. Trehalose: "Mushroom sugar, also called mycose, a disaccharide of glucose. Found in some fungi (Amanita spp.), manna, and some insects; hydrolysed by the intestinal enzyme trehalase"
  19. Expression Profiles: "The range of genes expressed at particular stages of cell development. The level and duration of expression of one or more genes in a particular cell or tissue (detected, e.g., via sample sequencing, serial analysis, or microarray‐based methods)"
  20. Principal component analysis: "Mathematical technique for condensing a metabolomic spectrum to a single point on a graph, permitting rapid comparison between different species, experimental and control groups, etc."
  21. Biosynthesis: "The production of a chemical substance by a living organism"
  22. Monod kinetics: "An unstructured model used to describe the correlation of substrate concentration with microbial growth kinetics"
  23. Acetyl coenzyme A: "a compound formed by the combination of an acetate molecule with coenzyme A. Acetylcoenzyme A has an important role in the Krebs cycle."
  24. Synthesis: "The combination of discrete items to form a new whole, such as the development of new ideas from existing ones, or the combination of separate elements to form a new complex product, synthetic chemical compound, or material"
  25. Adenine: "A purine derivative. It is one of the major component bases of nucleotides and the nucleic acids DNA and RNA."
  26. Endogenous: "A product or an activity that arises in the body or cell, in contrast to exogenous agents or stimuli that come from outside."
  27. Heterogenity: "not originating within the organism in question"
  28. biomass: The total mass of all the organisms of a given type and/or in a given area; for example, the world biomass of trees, or the biomass of elephants in the Serengeti National Park.
  29. prototrophic: any strain of a microorganism (alga, bacterium, or fungus) that does not require any substances in its nutrition additional to those required by the wild type
  30. dilution rate: the rate, F, at which existing medium is replaced with fresh medium in a continuous culture, divided by the volume, V, of the culture

Outline

Intro

  • Organisms undergo natural temperature cycles throughout a day and night cycle.
    • It is uncertain if organisms are able to adapt and acclimate within a 24 hour cycle, or if they deal with “continuous temperature shock”.
  • Saccharomyces cerevisiae were used in this experiment.
    • This mesophilic microorganism's optimal temperature is 33°C.
    • They are being studied because they are often used in sub-optimal temperatures in industrial applications, such as brewing and wine making.
    • Temperature ranges vary by strain, but this strain is able to grow in the range of 4°C and 40°C
  • While previous studies focused on different temperature analysis on heat and cold shock responses, this study used analysis of a continuous diurnal temperature cycle (DTC) to see if the responses can be predicted from steady-state analysis.
  • Other more recent studies have focused on the impact of this DTC on yeast glycolysis, but this study is investigating the overall physiology of S. cerevisiae.

Materials & Methods

  • The prototrophic haploid yeast strain Saccharomyces cerevisiae CEN.PK113-7D (MATa) was used in this study.
    • Kept in an anaerobic controlled environment
  • Sequential batch reactors were used instead of single batches because of enhanced reproducibility of certain growth rate measurements in the SBRs.
    • After three volume cycles, (not sure what this means) with no significant changes in biomass, a sinusoidal temperature cycle began.
    • Small samples of less than 5% of reactor volume were taken from the fifth and/or sixth temperature cycle in intervals of at least three hours.
  • Analytical analysis methods included gas and biomass analysis, total cell concentration, cell size, and residual glucose and metabolite concentrations.
  • The rate of glucose consumption during DTC was calculated.
  • Determined the budding index or percentage of cells carrying a bud.
  • The cell cycle phase distribution in the yeast population was analyzed.
  • 13 microarray analyses were taken from the DTC population, while 4 microarray analyses were taken from the two steady-state populations.
    • The genes with a P-value lower than .002 were considered significantly changed.

Results

  • The biomass concentration remained constant throughout the DTC, while CO2 production revealed a clear cyclic variation in fermentative activity.
    • The decrease of temperature from 30°C to 12°C correlated with a decrease in CO2 production.
  • After three cycles, the fluctuation of CO2 production and residual glucose concentration decreased due to the acclimation of the yeast cells to the DTC.
    • This residual glucose concentration was found to have an inverse correlation with temperature.
  • CO2 production and glucose concentration were found to have an asymmetrical rate of decrease.
    • The concentration of glucose decreased much faster when the temperature was increasing passed the temperature minimum than when the temperature minimum was being approached.
    • This asymmetrical relationship was also found in the CO2 production.
  • Extracellular metabolites were not affected by the DTC with the exception of acetate, which saw a rhythmic variance of 70% that mirrored the DTC.
  • A transcriptome analysis was performed 6 times throughout the 24 hours DTC.
    • The results showed mild physiological changes, but microarray analysis revealed major gene reprogramming.
    • 1102 genes showed transcription changes, and these were seperated into 6 clusters based on transcriptional induction/repression.
    • 3 clusters had their transcript levels peak at the lowest temperature, while 2 other clusters have their lowest transcript levels at the lowest temperature.
    • The final cluster didn't change when the temperature decreased, but had a strong increase in transcript level as the temperature began to rise again.
  • DTC specific genes were filtered out through a process of stringent criteria.
    • 692 genes were found to be either upregulated or downregulated by high residual glucose concentrations.
    • These 692 were removed from the set, giving a new total of 410 possible DTC specific genes.
    • Two studies were consulted to give the final narrowing of the genes.
    • Those that were reported in the other studies to respond to glucose were removed from the data set, and the final count was 253 genes considered to be DTC specific.
    • These 253 genes belonged to six main cellular processes and were spread throughout the six clusters.
  • Cell cycle was found to be controlled by 3 transcription factor complexes.
    • While temperature was decreasing in the DTC, there was a 22% decrease in cell number and 16% increase in cell size.
    • This inverse of this was found as the temperature increased.
    • Budding index is the percentage of cells carrying a bud, and it was found increase as the temperature decreased and vice versa.
  • In order to test the acclimation ability of this strain of yeast, it was grown in either a steady-state or constant 30°C or 12°C environment.
    • All physiological characteristics resembled the data from the DTC grown yeast with the exception of glycogen content.
    • The Monod equation was used in order to get a realistic comparison of the residual glucose concentration between the steady-state and DTC populations.

Discussion

  • The most prominent variation throughout the study was that of the residual glucose concentration. This was also observed in the steady-state glucose limited cultures through an equation relating residual glucose concentration to maximum specific growth rate, dilution rate, and the microorganism's substrate saturation constant for glucose. The residual glucose concentration can have a big impact on yeast glycolysis and more importantly the transcriptome of yeast. In order to prove that fluctuating glucose concentrations impacts extend past glycolysis, all of the genes that showed a response to glucose were removed. The Monod equation was used to predict the residual glucose concentration in the steady-state and DTC populations. However, these concentrations were also measured straight from the populations, as this was just a confirmations of the data obtained from the experiment.
  • Removal of glucose dependent genes reveals strictly DTC-responsive genes, many of which are related to the cell cycle. This suggests that the cell cycle may mediate cyclic adjustments to DTC via genetic “reprogramming.” However, removal of glucose-dependent genes may have also removed genes that are also responsive to glucose. What is more, changes in expression of genes involved in purine biosynthesis were shown to be affected by temperature. This suggests a possible involvement of purine synthesis with DTC-induced adjustments to gene expression.
  • The development of cyclic genetic adjustments seen over time (as well as cell cycle related genes), as well as their return to normal upon DTC cessation, suggests that cell cycle dynamics are not based on a circadian rhythm, but rather cell cycle dynamics. Relative specific growth rate is the determinant of genetic expression under DTC, not absolute specific growth rate or temperature directly.
  • Lack of direct correlation of trehalose along with glycogen concentrations suggest that temperature does not directly induce genetic expression changes related to carbohydrate storage. The dynamic may be more complex and may be beyond the scope of this study.
  • Most differences between DTC and SS were seen at 12 degrees C. Relevant genes for lipid biosynthesis, stress response, arginine biosynthesis, and some cell functions are thus important here. ER-to-Golgi transport and purine biosynthesis genes different at this temperature suggest that the temperature characteristics, rather than temperature directly, induce genetic adjustments.
  • As an interesting note, very few genes under DTC responded similarly in transcription levels when compared to rapid cold shock (only 10 genes). In these cases, the de novo purine biosythesis universal downregulation was always seen, and suggests that purine sythesis is very important for cellular responses to temperature change. Those gene upregulated and involved with zinc homeostasis, show the importance of zinc ions in physiological responses to temperature changes.

Questions

  1. What is the main result presented in this paper?
    • The DTC led to a partial synchronization of the cell cycle of the yeast population being grown in the cultures. This is most likely due to the imposed fluctuations of relative growth rate rather than a direct result of temperature. The yeast also acclimated its physiology and transcriptome to the differing temperatures throughout the DTC.
  2. What is the importance or significance of this work?
    • Little work has been performed previously to understand how organisms cope with 24-hour changes in temperature. Many organisms experience constant, predictable cold shock, and understanding how they adapt to routine cold shock provides information on how organisms deal with cold shock in general.
  3. What were the limitations in previous studies that led them to perform this work?
    • Previous studies involving the yeast examined the effects of glucose stress on gene regulation by varying the amount of glucose present in the medium, which lead this group to control the glucose present in the medium in their experiments.
  4. How did they treat the yeast cells (what experiment were they doing?)
    • Yeast cells were kept in constant temperature of 30 degrees Celsius without significant changes in biomass for three volume changes, then subjected to a programmed temperature cycle to mimic that of a normal, 24-hour Circadian cycle, with measurements of CO2 production, biomass dry weight and other metabolite concentration measurements taken during the fifth or sixth temperature cycle experienced.
  5. Draw a diagram or flow chart of the experimental design.
    • Diagrammoki.jpg
  6. What strain(s) of yeast did they use? Were the strain(s) haploid or diploid?
    • Saccharomyces cerevisiae is a haploid strain of yeast used in this study.
  7. What media did they grow them in? What temperature? What type of incubator? For how long?
    • The strains were grown an anerobic, glucose-limited chemostat culture. Sequential batch reactors were used instead of single batches. The strains were grown in three different temperatures: 30°C steady-state, 12°C steady-state, and a 24 hour diurnal temperature cycle from 30°C to 12°C. The cultures subject to the DTC were grown and stabilized at 30°C before the cycle was initiated. They were left in for 7 full temperature cycles.
  8. What controls did they use?
    • The medium was kept at a constant pH of 5.0, anaerobic conditions were maintained by continuous addition of pure nitrogen to the medium, and steady state cultures were grown in constant temperatures of 12 and 30 degrees Celsius when measurements varied by more than 5% for three consecutive volume changes.
  9. How many replicates did they perform per treatment or timepoint?
    • The paper states that samples were taken during the fifth or sixth temperature cycle and at at least three hour intervals. 13 microarrays were taken from the DTC populations, while 4 microarrays were taken from the steady-state populations.
  10. What method did they use to prepare the RNA, label it and hybridize it to the microarray? (very brief description)
    • Processing of samples, RNA isolation, and microarray analysis were performed as previously described in Mendez et al. (2013).
  11. What mathematical/statistical method did they use to analyze the data? (very brief description)
    • This study used the budding index in order to find the amount cells carrying buds. They also used the Modon equation and biomass equations to find the residual glucose concentrations.
  12. Are the data publicly available for download? From which web site?
  13. Briefly state the result shown in each of the figures and tables.
    • Figure 1: The first figure is the sinusoidal function curve of temperature imposed on the cultures. It was designed to mimic a natural 24 hour temperature cycle with the range of 30°C to 12°C.
    • Figure 2: The second figure displays a constant biomass throughout the DTC. However, the CO2 production and residual glucose concentration were found to have a correlation with the DTC. As the time went along, the amplitude of the peaks of fluctuation decreased, representing acclimation to the temperature cycle.
    • Figure 3: The third figure shows the physiological characterization of this strain of yeast under the set conditions. Biomass concentration and all of the extracellular metabolites, other than acetate, were found to be unaffected by the DTC. Acetate had a rhythmic variation of around 70% throughout the cycle. In addition, glucose concentration was found to have a higher rate of decrease when the temperature was increasing than the rate of increase as the temperature was decreasing. The inverse trend was found in the off-gas CO2 profile.
    • Figure 4: The microarray revealed major gene reprogramming that could be clustered into 6 unique groups. 3 of the groups were found to have peak transcript levels at the lowest temperature. 2 of the groups were found to have their lowest transcript levels at the lowest temperatures. The final group was not strongly correlated with the temperature cycle.
    • Table 1: Each cluster was tested for gene functionality, and the results are shown in the table. Some clusters had unique gene functionality characteristics, while other clusters had a large amount of differing gene functionality.
    • Figure 5: Two previous studies were consulted in order to remove the genes that were found to be glucose-responsive. 410 genes were found to be DTC specific, while 692 were found to be glucose responsive.
    • Table 2: The DTC specific genes were separated into six main cellular processes including: lipid metabolism, endoplasmic reticulum (ER)-to-Golgi transport, RNA polymerase III transcription, one-carbon metabolic processes, amino acid metabolism, and cell cycle progression. Of importance are the three transcription factors, Swi6, Swi4, and Mbp1, that are involved in the cell cycle.
    • Figure 6: The yeast population was shown to delay cell division when the temperature decreased, but the cell size still grew. The budded cells increased with the lowering of temperature, and as the temperature rose back up, the buds were released.
    • Figure 7: Four separate graphs relating to changes in metabolism of storage carbohydrates during DTC. Part A shows concentrations of stored carbohydrates within the yeast during the cycle. Part B shows the concentrations of key metabolites. C shows expression of genes associated with enzymes involved in storage carbohydrate metabolism. Part D shows residual glucose concentration, qs, budding index, temperature, and cell cycle distribution.
    • Figure 8: Average expression levels of all genes at each sampling point projected onto the first and second principle components.
    • Table 3: Comparison between the average values of steady state cultures and DTC cultures. Compares the average values at 12 and 30 degrees for various physiological characteristics.
    • Figure 9: Change in expression levels of 83 genes was more pronounced in DTC than in the acclimated cultures. The majority of genes responded to temperature with similar magnitude, and 20 genes did not reach full acclimation levels at 12 degrees Celsius.
  14. How does this work compare with previous studies?
    • This work is similar to some other studies, but it is unique in the fact that it is looking at the analysis of a continuous diurnal temperature cycle (DTC) and its effect on the overall physiology of yeast. The previous studies focused either on only heat/cold shock response, or DTC effect on yeast glycolysis.
  15. What are the important implications of this work?
    • This study showed that organisms are capable of adapting to almost peak levels of gene expression for cold shock and heat shock tolerance in the presence of a DTC, with only a few genes not reaching full acclimation levels at colder temperatures.
  16. What future directions should the authors take?
    • Future experiments could evaluate if certain environmental factors or resource abundances could result in full acclimation of an organism to cold shock conditions in a DTC. Other variables that exist in a 24-hour cycle, such as changes in moisture and light exposure could also be analyzed to determine their effects on cold shock adaptation.It would also be interesting to not only explore other strains of yeast, but other eukaryotes as a whole to see if these characteristics can be found in other organisms.
  17. 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?
    • The Monod equation was not well explained and seemed unnecessary to the paper. It seemed like the equation was a predictor of residual glucose concentration, but this concentration was already known from the data analysis of both the DTC and steady-state populations. It was a redundant, unnecessary piece of data. Another piece of redundant data was the information about the enriched function of the genes. These functions were shown in three different figures, and they could have been condensed into one much simpler figure.

Presentation

A copy of our Journal Club presentation can be found here

Acknowledgements

  • I would like to thank my partners, Mia Huddleston, Matthew R Allegretti, and Colin Wikholm, for the assistance on this weeks project both in the understanding of our paper in class and completion of the powerpoint outside of class.
  • The outline found on this page was completed with the mutual assistance of all four group members.
  • I would also like to thank Kam D. Dahlquist, Ph.D. for providing the instructions and information for this assignment both in class and on this document: BIOL368/F16:Week 14.
  • Even though I worked with the people noted above, this individual journal entry was completed by me and not copied from another source.
  • Matthew K. Oki 14:29, 5 December 2016 (EST):

References

  1. BIOL368/F16:Week 14
  2. Hebly, M., de Ridder, D., de Hulster, E. A. F., de la Torre Cortes, P., Pronk, J. T., & Daran-Lapujade, P. (2014). Physiological and transcriptional responses of anaerobic chemostat cultures of Saccharomyces cerevisiae subjected to diurnal temperature cycles. Applied and Environmental Microbiology, 80(14), 4433-4449. doi: 10.1128/AEM.00785-14
  3. Kwong, P. D., Wyatt, R., Robinson, J., Sweet, R. W., Sodroski, J., & Hendrickson, W. A. (1998). Structure of an HIV gp120 envelope glycoprotein in complex with the CD4 receptor and a neutralizing human antibody. Nature, 393(6686), 648-659. DOI: 10.1038/31405
  4. Müller, F. (2009). Assessing Antibody Neutralization of HIV-1 as an Initial Step in the Search for gp160-based Immunogens (Doctoral dissertation, Universität des Saarlandes Saarbrücken).
  5. Tran, E. E., Borgnia, M. J., Kuybeda, O., Schauder, D. M., Bartesaghi, A., Frank, G. A., ... & Subramaniam, S. (2012). Structural mechanism of trimeric HIV-1 envelope glycoprotein activation. PLoS Pathog, 8(7), e1002797. http://dx.doi.org/10.1371/journal.ppat.1002797
  6. Wilen CB, Tilton JC, Doms RW. HIV: Cell Binding and Entry. Cold Spring Harbor Perspectives in Medicine. 2012;2(8):a006866. doi:10.1101/cshperspect.a006866.

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