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.
Cameron Togrye
ReplyDeleteArticle 18 / EGFR signalling
0. Knew: Prototypical receptor tyrosine kinases (such as ERBB1) function in multiple pathways including GRB2-Ras pathway which activates MAPK activity and the PI-3K/Akt pathway.
1. Learned: I wasn't aware that ERBB ligands, which are related to EGF, are all produced initially as transmembrane proteins and don't become extracellular signals until they are cleaved at the membrane in response to a signal.
2. Pressing: How does this system of signal release operate? I'm familiar with regulated vesicle fusion to release signal molecules (as in insulin release) but these seems wholly different. How do these EGF-like domains not interact with cells via contact-dependent signalling before they are cleaved? Also, if this bow tie architecture is supposed to have redundancies, why did knocking out ERBB1 result in non-viability?
3. Presentation: Autocrine mechanism and its role in cancer (and healthy cell) signalling
4. Thoughts: I am curious of how all of how all this modularity which causes signal cascades that end up operating through the core processes can then be differentiated in the bottom part of the bow tie.
Tim Lee
ReplyDeleteAsgn_23A
0. Knew: Basics about cell signaling.
1. Learned: ERBB network and its widespread influence on multiple systems. Overview of bow-tie architecture in understanding a systems perspective of ERBB network. Overall robustness of ERBB network and impact if the network is disturbed.
2. Pressing: How will the bow-tie model incorporate other cell signaling pathways (G-coupled protein receptors, cell-adhesion machineries, etc.) that have yet to be modeled with the ERBB network?
3. Presentation: Comprehensive overview of EGF signaling pathway and ERBB network.
4. Thoughts: The article was a very intensely thorough overview of EGF signaling and I appreciated how the authors addressed the big picture significance of being able model and predict the network.
Juan Gnecco
ReplyDeleteAsgn_23A
Knew: Stan Cohen got the nobel price for EGF and EGFR signaling. HER2 is a particular growth factor key in determining breast cancer prognosis. Some of the signaling cascades of ERBB2.Regulation of signaling by negative and possitive feedback.
Learned: The mechanistic details and current knowledge of this signaling. Also the different types of ERBB and how each might be used to regulate signaling in each own way. How networking and system biology can be used in receptor signaling modeling.
Pressing: Bow tie model seems too simple and does not consider the redundancy in other signaling pathways that have the same signaling partners and downstream results.
Presentation: Detailed EGF signaling pathway and network analysis for this particular protein.
Throughts: Good reference to the biological effects and structural review of ERBB. Is the signaling the same through out all epithelial cells for example and how could this be modeled when alternative pathways and secondary signaling and receptors are present? Will these models consider SNPs?
Kate Jones
ReplyDeleteAssignment 23A Article 18
Knew: tyrosine kinases, formation of dimers upon ligand binding, some cell signaling pathways mentioned, positive feedback loops often coupled with negative feedback loops
Learned: redundancy of ligands, I didn't know anything about the ERBB network or its connection and targeting in cancer treatment
Presentation: I like the bowtie model in Figure 1 that simplifies a lot of the text about the ERBB network. Box 3 (Figure 5?) to show the connection with cancer therapy.
Thoughts: I like that this paper ties together some of the topics we had been reading about in earlier papers. Figure 1 shows positive and negative feedback loops, steady states and bistability, transcription factor levels determining cell fate
Kendra Oliver Assignment 23A Article 18
ReplyDelete0. Knew: Signaling of ERBB receptors.
1. Learned: Modeling approaches to orchestrate signaling derived from ERBB signaling. Concept of a two-compartment model for receptor internalization where receptors. Able to include ligand affinity for signaling efficiency. Modeling from low-affinity mutant of EGF that is able to increase recycling of receptor.
2. Pressing?s: How would you account for signaling noise from outside signaling activation? What is the baseline activation state of signaling partners and how would this change the model? If you consider different affinities for ligands, should you also consider signaling bias of the receptor for specific conformational states? Signaling from internalized receptors (Ex. for GPCRs arrestin)?
3. Presentation: Application to GPCR signaling.
4. Thoughts: I think this is a good starting point for understanding the signaling system but there are major caveats to modeling this system in isolation and predicting cellular outcomes.
Zach Bednarke
ReplyDelete23A, 18
0: Knew nothing about ERBB receptors, nor did my friends who have taken intro Bio here- is it usually covered?
1- Learned attempts made to model ERBB receptors at systems level. The 5 characteristics of robustness, as listed in this review. Many physiological functions of each of the receptors. Role of ERBB deletions in cancers.
2- im interested in the mechanisms evolved to attenuate signals. Are phosphorylation and degradation the main ways signal proteins are removed?
3- In depth mechanism for one protein, following it through figure-1.
4- I think this is very in depth and requires a second reading on my part- this represents a part of biology that I havent see yet, as it is new in this class and this is my first real bio class. But I look forward to the next articles and a more detailed approach that provides examples
Chuck Herring
ReplyDeleteAsgn_23A
Knew: Very little about EGF-ERBB signaling.
Learned: That a systems approach must utilized when studying the EGF-ERBB signaling pathway.
Pressing: Is the robustness of this pathway unique?
Presentation: Detailed EGF signaling pathway review.
Thoughts: A lot of detailed information to take in, but really liked how they worked from structural biology up to a systems approach.
Arman Chowdhury
ReplyDeleteAssignment 23A
0. Knew: Cellular receptors involved in signaling of cancer are often targeted by cancer drugs
1. Learned: ERBB signaling includes modularity, redundancy, and plays a role in combinatorial interactions in signal diversification; ERBB1 has a pivotal role during epithelial cell development in several organs; ERBB2 is a non-autonomous amplifier; ERBB3 is kinase defective but can recruit P13K to distinct sites; ERBB4 similar to ERBB1. Overexpression of ERBB receptors has been correlated with proliferation of several kinds of human cancer. Mathematical modeling of the ERBB signaling could lead to much better understanding of its dynamic network.
2. Pressing: The definition of modularity provided on the paper seems incomplete, and I am still not clear about the term and how ERBB networks show modularity to increase their robustness.
3. Presentation: Figure 1 is an elegant representation of the bow-tie architectural network of ERBB signaling. It clearly shows ligand-receptor interactions, signaling pathways, inputs, outputs, and positive and negative feedback loops.
4. Thoughts: The paper talks about the trade-off between the robustness and network fragility of ERBB signaling, and I think it’s interesting that researchers are now targeting fragile points of the ERBB network inherited by tumors for cancer therapy. But I wonder how researchers would control allowing degradation of the tumor ERBB receptors while preventing degradation of the normal body cell ERBB receptors.
Mark Vander Roest
ReplyDeleteAssignment 23A
0. Knew: Basics of the EGFR pathway, implications for disease and potential for modelling.
1. Learned: A lot of review since I read the paper 2 years ago, but very helpful review for sure.
3. Presentation: Good overview of EGFR signalling
4. Thoughts: It seems like a huge hairball of signalling. I'm glad that I'm not currently working with such a massive network.
Cami Johnson
ReplyDeleteAssignment 23A
0. Knew: How tyrosine kinase receptors worked, that malfunctions in the EGFR pathway can lead to cancer (specifically with HER2 receptors in breast cancer)
1. Learned: The different roles and characteristics of the various ERBB receptors and what makes EGF-ERBB signaling robust
2. Pressing ?: I don't fully understand the advantage of the bow-tie architecture, is it similar to functional redundancy?
3. Presentation: consquences of EGF-ERBB signaling mutation
4. Thoughts: I'd heard of this signaling pathway before, but didn't know the details. I thought it was particularly interesting that ERBB2 essentially acts as an amplifier without its own specific ligands to bind to.
James Pino
ReplyDeleteAssignment 23a
0:Knew: ERBB family is related to proliferation control.
1:Learned: I did not know the diversity between ERBB(1-4).
2:Pressing: Does a model including ERBB pathway including all the branching pathways exist (mathematical model)?
3:Presentation: Network free simulations, how to deal with complexity of nearly infinite states of ERBB signaling.
4:Thoughts: The statement "As mathematical modelling constitutes the heart of
systems biology" is interesting.
Selene van der Walt
ReplyDeleteAsgn_23A
Knew: Control circuits are often the target of drugs, particularly any network weaknesses, because by targeting this you can affect several downstream effects.
Learned: about the specifics of the ERBB signalling pathway, as well as the evolution of a robust signalling network and how it applies to ERBB in that it maintains its modularity and redundancy. I also learned that we currently have the technology to simeltaneously monitor all 89 sites of the interactome of the network.
Pressing ?: Is there anything unique about the bow tie nature of this network? It seems to me like most signalling networks would fall into this pattern. The bowtie shape also seems somewhat contrived since it is formed simply by condensing all the numerous core processes into one 'narrow' middle section.
Presentation: How changes in control of signalling networks caused by diseases such as cancer can have large downstream effects.
Thoughts: I am still unclear on how the fragility of a network is determined. Is it simply decided by how likely the network is to be disrupted by some outside force (ie. cancer)?