log.txt

__TOC__

==March 8, 2014==
1431
BA2220

<h4>Project Repository</h4>
Created project repository on GitHub.
[https://github.com/ehsueh/ShmooS.git see link] 

<h4>Reading summaries</h4>

I. Triggering of Pheromone Signaling Pathway
:1.pheromone binds to Ste2 (GPCR)
:2.triggers G_alpha to release G_beta and G_gamma
:3.G_beta_gamma has 3 effectors:
::a.Ste20 associates with Bem1 and localize to membrane by binding with Cdc42
:::*Bem1: involved in establishing polarity (binds Ste5, Ste20, Cdc42, Cdc24)
::b. Ste5 and Cdc24 which further triggers cascade leading to gene expression involved in matting response.
::c. Far1-Cdc24 complex 
:::*Cdc24: a GEF for Cdc42-GDP--> Cdc42-GTP
:::*Far1: inhibits cell-cycle progression (MAPK substrate)

II. Recycling mechanisms of Cdc42
:1. Fast - mediated by a guanine nucleotide dissociation inhibitor (GDI) called Rdi1
:2. Slow - endocytosis process mediated by actin patch

See [https://github.com/ehsueh/ShmooS/blob/master/stats.txt stats.txt] file for details.

<h4>Ideas for Abstraction</h4>
Some crude ideas:
:1. Graph: take all proteins/ biofactors involved in the pathway as the node set. There exist an edge if an interaction of a specified type exists. (e.g. there is an edge from Cdc42_i to Ste20_j if Cdc42_i binds to Ste20_j) 
:2. Matrix: Each protein type involved will be represented by a m by 3 matrix where m is the number of proteins of that type. I.e. row r of Cdc42 matrix represents the rth Cdc42 which is located in the cell by the coordinate (Cdc42[r][0], Cdc42[r][1], Cdc42[r][2]).
:3. Visualization: Represent the cell as a 3-Dimension Coordinate Space like RGB colour space. I.e. RGB corresponding to x,y,z so the cell will be a (255,255,255) colour space. And if a protein is on the surface of the space, then R or G or B equals to 255.


==March 16, 2014==
1553
BA2220

1. Rdi1 is a Guanine nucleotide dissocation inhibitor (GDI)
2. GTPase cdc42 mediates symmetry breaking
3. different prots accumulate at restricted region of membrane to initiate morphogenetic downstream cellular activity at that site --> this clustering:
:::a. can occur without presence of spatial cues 
:::b. is in dynamic equilibrium (clusters remain stable but there is rapid exchange btwn prots in cytoplasm and those at the membrane)
4. Two pathways identified for Cdc42 localization:
:::1) involving targeted excocytosis of cdc42 along actin cables
:::2) fast recycling of cdc42 by Rdi1
5. Exactly how the two pathways interact with and affect each other are unknown.
6. Constitutively active or inactive Cdc42 polarization can not occur without actin; GTP-bound <-> GDP-bound cycle is crucial for actin-independent polarization.
7. "Fundamental mechanism responsible for spontaneous polarization still remain controversial."
8. Modeling experiments in the past:
:::1) With only one postive feedback loop:
::::-unstable polarization
::::-reduced polarization efficiency 
::::-smaller stochastic effects with increasing number of particles
:::2) Goryachev + Polkhilko's turing-type mechanism: 
::::- proposal: GDI-mediated polarization clusters result in multiple short-lived clusters which are merged into one single cluster due to competition for limited amount of prots
::::- wet lab experiments detected multiple transient caps in wild-types
::::- BUT, recent study shows that formation of multipe stable clusters is due to actin and that GDI-mediated polarization counter the formation of multiple clusters
::::(Side-note: turing mechanism = interaction bewteen inhibitors and activators resulting in complex patterns)
:::3)This paper's approach:
::::- deterministic reaction-diffusion dyanmics
::::- results have been verified experimentally
::::- gives precise spatial and temporal control of cdc42-gtp production => can accurately initiate developmental processes at specific time and place 
::::- explicitly include concentration and distribution of Cdc42, cdc24 and bem1
9. Positive feedback loop: how GEF Cdc24 is recruited towards Cdc42-GTP is not entirely known (controversial). Contributors include: p21-activated kinase Cla4 and Bem1.

<h4> TO-DO's </h4>
* Update Boris about progress
* Meet with Dr. Sergio Peisajovich
::- ask questions about the pathway
::- are we understanding the bio side correctly?
::- are we overlooking anything important?
::- do the stats we collected look reasonable?
* Talk to math profs (laplace operator model.... etc)


==March 20, 2014==
1700~1830 ish
* Discussed equations used in Ben Klunder et al.'s paper "GDI-Mediated Cell Polarization in Yeast Provides Precise Spatial and Temporal Control of Cdc42 Signaling"
* Met with Professor Arick Shao to ask questions about the math
:- Laplacian
:- Laplace transformation
:- Heat equations

==March 23, 2014==
1434
<h4> Modelling </h4>
* Dynamic equilibrium: exchange of proteins at cluster
:- right below cluster: lower cytosolic concentration
:- around that, higher cystolic conc
:- net flux from cytosol to membrane at the center of cluster
:- opposite flux at periphery => total # of prots in cluster remains constant
:- continuous prots redistribution to counter lateral diffusion along membrane (see mass conserved polarity models)
* positive feedback loop
<h4> Emergence of Polarization </h4>
* linear stability 
<h4> Expectations </h4>
* "reduced values of any of the parameters (Cdc24, Bem, Cdc42...) will prevent polarization
* increase in GEF conc --> reduce in Cdc42 hydrolysis rate
* growth of cap = linear change in conc
* narrowring of cap = non-linear
<h4> Matlab script</h4>
Questions + concerns:
* Laplace operator: what is our concentration function? Are we missing something?
* How to represent positive feedback loop?
* see github shmoos.m