User:Pakpoom Subsoontorn/Notebook/general reading/2008/11/09

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Strategic Summary: week of 11/16/08

  • Now, I start weekly planning and time-table

Genetically Encoded Memory

  • Meeting with Drew and recap the goal about recombinase studies. I have been researching on recombinase enzymes. There are two related aspect of studies that I'm interested in
    • Potentially to be used as a tool for our genetically encoded memory: making specific change in DNA
    • To develop a new paradigm for standardizing biological Parts. Single-enzyme parts like this will be a very low level part, in oppose to something like a circuit. I would like to have a catalog of items (recombinase) with similar properties (joining two pieces of DNA)..that we can compare and contrast their key properties. The important questions are: what should be key properties to compare? how do we get them? How do we get them QUICKLY? Let's break down into five areas
      1. Prioritizing Questions and information:
        • We don't have time, money and manpower for answering every single detail questions. Still, we don't have to know everything before engineering something
        • We surely want to know the substrate, auxiliary factor requirement, specificity, efficiency, speed...topology limitation..we might not care much about sub-molecular mechanism (like who transfer electron to whom..), phylogenetic, etc.
        • To what extend can we treat things as blackbox?
      2. Database and literature mining
        • We cannot read every single paper popping up in google scholar search in detail. Still, we gonna have to read a lot of them.We need systematic way to look for and grasp relevant information.
        • What are known, unknown, or not sure?
        • I think there should be lots of useful tools we can borrow from system biology..the way that they identify and annotate a new gene or protein.
      3. Developing higher throughput assay/ better measurement for characterizing recombinase enzymes
        • From those paper I read, there're common method for identifying minimal target sequence, measuring efficiency, etc. I think many of them can automated ...and assay under standard condition
        • We could learn from other high throughput characterization like chip-CHip or oxygen consumption assay. ..Berkeley iGem'08 project
      4. Constructing custom integrative database..combing our assay results and existing data we have dug out other studies
        • Again, I think there should be lots of useful tools we can borrow from system biology..the way that they identify and annotate a new gene or protein.
        • Right now I simple summarize whatever I read about each enzyme in separate pages on my OWW lab books
        • It's very important that we can compare and contrast items on our DB...how's this particular property of this recombinase compared to that recombinase? "properties" should include the information of whether we know or don't know a particular facts too. For example, we note that excisionase of lambda int has been identified (Xis) while that of PhiC31 is not yet.
      5. Synthetic studies: constructing genetically encoded memory system...at least the basic one.
    • In the end, we need to juggling around these five areas, more or less
  • Upcoming week
    • Reading on Fim and Hin system
    • Pubmed Tutorial and Journal alert
    • Summary Assay on minimal target sequences

Bacterial cell shapes

  • There are three projects I would like to finish (I mean get a chunk of presentable good data) by the end of this year
    1. How E.coli transform its shape at different phase of growth? How the rod shape turn into the round shape as the cells go from exponential growth phase to stationary phase, and vice-versa?
    2. Dynamics of E.coli cell cracking due to vancomycin
    3. Designing and testing the two new microfluidic chip
  • Now, let's look in detail how I will get there, (Next meeting let's discuss the calendar with KC)
    • Let's say I should be done for the rotation two weeks before the winter term start. I will have about 5 weeks to do the rest of works
    • Ask KC about the Chip, when will the first design arrive? For the second chip, I still need the answer about filling in the blank, about the hole, and about the shrinkage? What else can we do while waiting for the Chip? I guess not for the second one. For the first one, I think we might wanna check out the air pressure controller.
    • For the E.coli round/rod transform,
      • The review paper on cell-wall synthesis, Scheffers and Pinho 2005, refers to a couple of papers on how e.coli shape changes due to starvation. Read them!..I may also need to re-read Reshes et al 2007 in detail how they model the growth of E.coli cell
      • Carefully plan for experiment this upcoming wednesday. Can the software break the cell clumps? Will we use the 96 well gel array?..make sure that we book the microscope schedule for the the following weeks. Don't forget the grow cell on Tuesday!
    • For cracking experiment, can we do anything before the chip is done? if not, I think I should spend time on understanding KC's model...reproducing the figures in the papers
  • Let's start outlines for minireport on cell cracking and cell shape transformation. The outlines should be oriented around broad/narrow questions about the growth and the physics of cell walls (Socratic approach!). By the end of this week, I should be able to at least go the white board and tell the consistent story about what have been studies, current models, and what exactly we may achieve next

Strategic Summary: week of 11/09/08

  • This is the first research strategic summary I wrote. I will the origin, the purposes, the list of ideas and the current plan on my research at Stanford so far, at Drew Endy's lab and at KC Huang's lab. Note that this week summary is particularly long, as I have to give all the background. The summary next week and the following weeks will be shorter and focus on the current state of the project.

Genetically Encoded Memory

  • General interest
    • The big picture of my interests in this projects center around developing methods and managing guideline for discovering, characterizing, standardizing and presenting biological parts: enzymes, transcription factors, biochemical circuits, etc.
    • While the size of "registered biological Parts" library of BioBrick foundation is rapidly increase, there are two important facts one needs to keep in mind.
      • First, most of the registered parts came from specific studies from individual research groups. Synthetic biologists develop and characterize a set of parts they would like to used in the biological machines. Then, that data is put together and presented in BioBrick "standardized" format. Thus, the new Part arises in the library as a result from a specific engineering project.
      • Second, billions years of evolutions have created huge diversity in living universe, which, of course, include the large library of naturally derived "parts"--enzymes, transcription factor, biochemical circuits, etc. Only a tiny fraction of these Parts are characterized well enough so that synthetic biology start using them to build something new. For instance, recall how many "transcription factors" and "promoters" have been identified...versus how many are frequently used by synthetic biologists to build a new living machine.
    • I believe that it would be very useful to have a synthetic biology project that focused on large-scale characterization of these natural parts for engineering purpose. I realized that there are three major issues to be addressed
      • Prioritize question and information: we don't have to know everything about a part before using for engineering. Also, in practice, it might take natural scientist decades to dig deep into detailed mechanism of something. We engineer cannot wait that long!
      • Data mining: if we wanna be tall, we need to stand on the shoulder of a giant! Generally, there are more or less valuable information about the Parts from previous studies. This information scatters around different database and publication. While not all conclusion and theories from the past are valid or usable for engineers, we shall not have to start learning things from scratch.
      • High-throughput assay and powerful measurement: we should be able to characterize multiple parts that belong to the same category all at once, under the similar standard conditions. This would allow engineers to compare and contrast items in the catalog. For instance, one might want to ask which transcription factors should I use in this circuit. Let's transciption X, Y, Z are all functions like inhibitors in nature..but different kinetic profiles, life time, etc. One may want to compare such information
      • Data representation: after all, whatever we did will be useful only if those who come after can use it. There are many ways to represent the collective information about part that we know. Again, I believe that the very important features of our presenting schema is the capability to compare and contrast thing in the same category (like comparing one DNA polymerase to another DNA polymerase.. comparing one transcription inhibition system to another transcription inhibiting system) and same attribute (compare the speed of all DNAP in catalog... compare inhibiting kinetic of all transcriptional inhibitors in the catalog)
      • Synthetic studies: it's important to demonstrate that the collection of data we present can facilitate the process of engineering a cells. In reverse, the result from an engineering project will also help us modify the methods and the management of the library of parts. Note that there can be many level of synthetic studies. Let's say we get the collection of information about DNA polymerase, that could help the protein engineering project on DNA polymerase..it could also help the circuit level projects that require DNA polymerase with specific properties.


  • Specific projects: Genetically encoded memory and site-specific recombinases
    • Original thoughts: In the past month, I have been oriented by studies toward the genetically encoded memory project at Endy's lab. The goal of that project is to engineer a system in which we can write, store and read out "the history" of a cells. "The history" in the general sense can be in environmental clues (like how many times the cell has been treated with IPTG or shocked with heat or light) or internal physiological state (like have many times have the cell divided). At this state of the project, we still enumeration different storage mechanisms. One possibility, though, is to store such information in the state of DNA. In this systems, the different history paths change the sequence of the cell differently. In the end, one can readout the sequence of DNA of the cells and know what history the cell has gone through. This can be done by having the cell express different reporters, if it has different DNA sequence. To do so, sequence modification may affect the gene itself..or affect the regulatory regions of a reporter gene.
    • I focused on the writing mechanism, thequestion of "how to change to DNA sequence" at a specific location in a living cell. We have learned one example from a recent publication from Arkin's group (PMID: 18665232) that inversion of DNA can potentially be used to store memory. In their system, the cell will expression different invertases upon the activation by different environmental clues, resulting in the different inversion patterns in the plasmid. Experimentally, they had the problem that their invertase reactions had relatively low yields and bidirectionality. Now the question is is there any more efficient system for changing DNA at specific sequences.
    • Starting with some reading on invertase and other related enzymes in site-specific recombinase enzyme family, I realized that these classes of enzymes have a great potential of being our writing tools. Hundreds of these enzymes have been identified even though only about ten have been heavily studied. Their capability to cut-and-exchange pieces of DNA has been widely exploited in construction transgenic organisms, genetic knock out and possibly gene therapy. Surprisingly, I haven' seen any public database that store the whole collections and reaction profiles of these enzyme, not that I saw any large scales study that compare and contrast their activity profiles. I imagine that it would be very useful to have the extensive database and the large scale studies of this class of enzymes, not only for our genetically encoded memory project but also for many other biotechnology that based on site-specific DNA recombination.
    • (More) Specific goal: Therefore, I planed to use "site-specific recombinases" as a specific study case for my general interest I mentioned above. In the project, "Parts" to be standardized in the whole collections of site-specific recombinase enzyme, natural or synthetic. I will be developing methods and managing guideline for discovering, characterizing, standardizing and presenting biological this class of enzyme.


  • Specific project in detail, current progress and plan
    • As I mention above, I hope that this project will have five related components
      1. Prioritizing Questions and information
      2. Database and literature mining
      3. Developing higher throughput assay/ better measurement for characterizing recombinase enzymes
      4. Constructing custom integrative database..combing our assay results and existing data we have dug out other studies
      5. Synthetic studies: constructing genetically encoded memory system...at least the basic one.
    • General self-comment: I would hope to get something "innovative" (which also mean something publishable and can become the core of my Thesis) from the #3 and #5. I would imagine that my #2 and #4 might mostly be about adapting of the existing tools for our purpose..but who know, I might end up making something new too. Also, #2 and #4 can be done right away while #3 and #5 I have to wait at least until the spring term to actually run experiment. #1 sounds very philosophical but I think it's very important to think about this question regularly and writing it down explicitly...we have to keep in mine that something is very hard to measure (to our limited time, tools, and understanding)..and something doesn't really need to be measured.
    • Now let's discuss each of the 5 components in detail.
      1. Prioritizing Questions and information
      2. Database and literature mining
      3. Developing higher throughput assay/ better measurement for characterizing recombinase enzymes
      4. Constructing custom integrative database..combing our assay results and existing data we have dug out other studies
      5. Synthetic studies: constructing genetically encoded memory system...at least the basic one.

Bacterial Cell shape

  • Right now there are two components of the project I'm working on
    1. Developing methods for monitoring the dynamics for cell shape/membrane organization.
    2. Modeling membrane dynamics
  • This would be a great chance for me to re-learn statistical mechanics, imaging and microfluidic design. In particular, I will juggling between experimental work for measurement and modeling work. Now let's see these components in detail
    1. Developing methods for monitoring the dynamics for cell shape/membrane organization. In the past, KC and his colleges have creates biophysical models of these dynamics. Some measurement have been made but in pretty rough resolutions, spatially and temporally. In the past week, I and KC have been working on "brute force" measurement of E.coli shape transition...how E.coli change from stationary phase's round shape back to exponential phase's rod shape? At Theriot's lab, We cultured cells in the tubes, took samples once in a while and image them on agar pads. In addition, I have been working on microfluidic design, using AutoCAD. I have designed two chips so far and still waiting for the feedback from the foundry. These chips will be used for monitoring cell division from a single clone inside a confined chamber.
      • Here is my questions and todo list for this part.
        • On time investment: KC's lab is still under construction ...and it will take awhile before we can get the microfluidic chip running. Should we invest significant amount of time optimizing the current "temporary" procedures, from agar pad making to microscope set-up at Theriot's lab to time management during each sample collection. My personal answer would be yes. Still, it will depend on how much data we plan to get here.
        • Also, experimental measurement and theoretical model need to go side-by-side..for every mini-project measurement, I do need to read and collect the related physical model. For instance, how the E.coli shape changes throughout the growth time? Mechanics of cell wall during cell division?
    2. Modeling membrane dynamics. Franking, I have never worked heavily on biophysical model before, and this one would be and interesting place to start, especially given the fact that KC's excited to chat about this stuff. Up to this point, I don't have a specific question to tackle yet. Mostly, I spend my time catching up with the background on biophysical model. Most of them are from the papers, which I found pretty hard to read. It would take some time before I'm comfortable rewriting such messy equations myself. Another thing that usually bother me is that most of the theoretical models go far beyond the measurement. Whatever kind of modeling I will choose to work on, I hope that I can come up with a set of feasible experiment/measurements to challenge it.
      • here is my todo list for this part
        • List specific modeling question to work with
        • Read and summarize existing models...let's start with Wiggin's review paper and Tristan's paper. I should be able to go the whiteboard and explain them the the audience.
        • Start collecting paper that involves quantitative measurement, relating to the models. Start listing the "frequently used trick" for measurement
  • Now, talking about theoretical model and experimental measurement going side-by-side, I think I should also divide my work into sub-projects centered around scientific questions (like dynamic of cell wall during the division, cell-shape transition, membrane bending, etc.) In addition to the division based on lab work (like chip design, imaging, modeling). I should also split my paper/reference collection this way too!
  • given that the lab is under construction, this is a good chance to experiment on organizing laboratory too. Here is some thing I wanna do (or propose that someone should do)
    • keep track of all inventory: microscope filter, spec, dye, cell line...have a good way to document each of them..what do we have, what the user need to know, scientific basis
    • Quick start and how to Video. For the method that we repeatedly use..or the one the will generate beautiful data..I wanna filming to the whole process and upload it somewhere. While I still keep written document protocol, this multimedia make the process much easier to understand. The written document should have hard-fact like numbers and names. The video can help explain things like..turning this knob ...or making agar patch



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