The Systems Biology of COVID-19 and the SARS-CoV-2 virus. The class will build a foundation that includes the emergence of complexity, simple biological subsystems, their reductionist and equivalent toy and organ-chip models, and the measurements required to specify model architecture and parameters. Applications to biology, physiology, medicine, chemical and biological defense, pharmacology, drug discovery, and toxicology. UGrad: PHYS 240 01 and BME 290B; Grad: PHYS 326 and BME 395C.
Monday, September 3, 2018
SysBio18 Asgn_2D_Class_4_Article_04_2018_09_04
Ultimate Yeast Model: Scan Article 04 Chen, K C,
Calzone, L, Csikasz-Nagy, A, Cross, F R, Novak, B, and Tyson, J J.
Integrative analysis of cell cycle control in budding yeast. Mol. Biol.
Cell 15:3841-3862. 2004. Think about what is involved in creating AND
VALIDATING this type of model.
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0: What I already knew
ReplyDeleteI have some familiarity with the cell cycle, its different stages and checkpoints, as well as its regulatory components. I also have a little exposure to the genetics of yeast and the developmental biology of frog oocytes.
1: What I learned
In this paper, I learned how Tyson constructed a quantitative mathematical model of the yeast cell cycle control mechanisms. For example, I learned that one assumption he makes is that he combines all cycles that have redundant functions to simplify the wiring diagram. In addition, it was interesting to find out that the modeler has some freedom in choosing how to model the cell cycle (option to use either algebraic or differential equations, and mass-action vs Michaelis-menten kinetics). Overall, there are three levels of assumptions that are made in these types of models. First, the wiring diagram overly simplifies the factors that model the system. Second, the math equations, and third, the specific rate constants assigned. Once the equations are then solved, he checks to see if the behavior of the model matches the behavior of the cell.
2: Pressing Question
Given the 61 different equations presented to describe the control mechanisms of the yeast cell cycle, the different components appear relatively independent in the math. How possible would it be to integrate all these equations together to provide a comprehensive model of the overall cell cycle rather than equations describing each independent reaction? Is the presentation of these equations technically reductionism?
3: Presentation Topic
Applying the modeling framework presented in this paper to DNA replication.
4: Thoughts
I thought it was interesting how Tyson notes that the goal, however, of these models is not to prove the hypothesized mechanism, but rather just show that the proposed molecular mechanism is a reasonable approximation of the yeast cell cycle. Thus, I'm curious to see if other cell biologists have proposed similar or differing models of these same biological phenomena.
0) KNEW
ReplyDeleteI knew a bit about using differential equations to model gene expression, since that's very similar to what I did this summer. I am aware of the difficulties of solving the interactions between different models/equations.
1) LEARNED
In all eukaryotes studied, cyclin B-dependent kinase drives cells into mitosis. Yet, all the other cell cycle phases are more diverse in how they occur throughout biology.
2) QUESTION
I guess I just don't know enough about proteome/cell analysis, so my question is why we can't determine the protein concentrations of all the relevant proteins in yeast. They said that they had to use arbitrary units for their concentrations. Isn't IM-MS helpful? Can we do secretome to figure this out? As a follow up, this article said Ghaemmaghami et al. (2003) published comprehensive protein expression data for yeast. Is this not integrated yet?
3) PRESENTATION
genotype to phenotypic varibility
4) THOUGHTS
This wasn't my favorite paper. It seemed very technical to me and took a while to get through. It would take a lot longer to go back through to get a full understanding with all of the small molecule names, but overall, I like that this paper created a model for the yeast cell cycle.
0. What I Already Knew: Have studied and seen differential equation models of biological systems in the past. Very little background in the cell cycle.
ReplyDelete1. What important thing I learned: The systems alternates between two states - the G1 state and the S/G2/M state. Been awhile since I've seen anything about cell replication. Models such as these must be tested by comparing the simulated behavior with that of mutants. The reason behind this is that the model was not designed to match the behavior of the mutants. These agreements validate the model more than behavior it was fit to.
2. Questions: What larger applications can this model be applied to? Why could they group certain proteins together in their model? I am also a little uncertain about where the mass model came from? Experimental data? When can we claim that a model is final/correct?
3. Class Presentation: Gene Knockout.
4. Thoughts: This paper was not the easiest read. As Caleb noted, the detail into molecular interactions was difficult without much more background in the material. I will likely need to reread this paper to get a better grasp on it.
0) Knew: Another good example of using a system of ODEs to model biological network interactions.
ReplyDelete1) Learned: They could create a model that was a good approximation of WT yeast behavior, then tweak it to model mutant strains and made reasonable predictions of their behavior compared to in vitro observations.
2) Questions: This is a good intracellular model, but how do you scale this up to encompass a system of cells of different types signaling to one another? Would you have to reduce the complexity of the equations or can you go about it almost the same way?
3) Presentation: Model scale-up