Ani Arun and Shirley Galbiati 20.109 Proposal

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Contents

Research Proposal Brainstorming

Scientific Questions and Engineering Goals

Inspired by the Hasty lab synchronized oscillator, we would like to construct a synchronized oscillator in mammalian cells. We would like to use this synchronized oscillator to form static spatial patterns of gene expression, as occurs naturally in the vertebrate segmentation process. Our project could shed light on the key processes that govern the vertebrate segmentation in development, as well as serve as a starting point for programmed patterned tissue formation and other applications in regenerative medicine.

In our implementation of the system, we would rely on fluorescent proteins as the readout of cell state. Experimental verification of our system would require time-lapse quantitative imaging techniques.

Background Information

This goal may require the use of a synthetic mammalian cell-cell communication mechanism. Thus far, none has been published. One idea is to use Delta and Notch signaling in cells that have the endogenous copies knocked out or knocked down. (More literature combing on this topic is needed). We would also need to come up with network topologies and a corresponding molecular implementation that could result in robust, synchronized oscillations. Finally, we hope that inspection of the current understanding of the role of FGF8 (fibroblast growth factor 8) in translating temporal segmentation clock pulses to spatial arrangement of segmentation boundaries will enable us to reach our pattern formation goal.

Update 5/3: Components needed for sequential segment patterning:

  • Moving morphogen gradient
  • Locally synchronized oscillation
  • Bistable switch (default state: high morphogen, "on" state (less sensitive to oscillation than morphogen). can be switched "off" at peak of oscillation and low morphogen.

Cool video: http://www.youtube.com/watch?v=p9Ogg8BJW8c&feature=related

Questions:

  • How to implement moving morphogen gradient?
  • How to implement synchronized oscillator?
    • Need mammalian cell-cell communication with minimal cross-talk
    • Need a way to regulate cell-cell communication
    • Need robust topology
  • How to couple synchronized oscillator to bistable switch in the simplest, most robust manner?

References

Oscillator review article (Dec. 2010): http://www.ncbi.nlm.nih.gov/pubmed/20934319 Goes over pretty much every synthetic oscillator implemented, starting with repressilator, to syncrhonized bacterial oscillator (hasty) and finally to various mammalian oscillators.

quote about challenges in creating synchronized mammalian oscillators: "Although synthetic mammalian oscillators have been shown to be robust, they provide tunable amplitudes and frequencies and enable activities with a 24 h rhythm, the production of a clonal population of mammalian cells whose clocks operate in synchrony remains a major challenge. While coordination of oscillations across mammalian cell populations using diffusible molecules could in principle be established according to the prokaryotic blueprint (Hasty) it is extremely difficult to produce stably transgenic mammalian cells with multiple oscillator components. This is because a reliable ‘plasmid system’ analogous to prokaryotes does not exist for mammalian cells and chromosomal integration of transgenes is completely random, lacks copy-number control and is prone to interference by neighboring sequences at the integration site. Also, to avoid interference between the oscillator components, they need to be placed at different sites on the chromosome."


"Bottum up tissue engineering" http://www.ncbi.nlm.nih.gov/pubmed/21524904

So much win in this paper, Charlie Sheen would be jealous. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2423395/?tool=pubmed

Mammalian control systems (doctoral thesis): [e-collection.ethbib.ethz.ch/eserv/eth:2385/eth-2385-02.pdf]

Quorum sensing molecules in different microorganisms: [1]

Wendell Lim 2010 paper "Designing customized cell signaling circuits" [2] Looks like a great review with many examples of synthetic perturbations to native signaling networks. Even includes synthetic notch signalling! I've only skimmed this so far, but it has a lot of potential in helping us nail down a genetic circuit to implement the general behavior outlined above.


theoretical paper on clock-wavefront model of segmentation (Francois et al, 2007)[3] Note: this model assumes a "1D" embryo (a line of single cells) and no cell-cell communication... Still helpful in understanding clock-wavefront dynamics.

Cis-interactions between Notch and Delta generate mutually exclusive signalling states David Sprinzak, Amit Lakhanpal, Lauren LeBon et al


In this project, Sprinzak et al. examined the Notch-Delta signaling pathway that allows neighboring cells to communicate during the developmental phase. Notch can be repressed by Delta in cis (on same cell) but is activated by Delta in trans (on different cell). The researchers used quantitative time-lapse microscopy to show that Notch levels in a given cell are much more sensitive to cis-Delta than to trans-Delta, creating an abrupt bistable switch: the cell is either exclusively a sender of Delta (high Delta, low Notch), or a receiver (low Delta, high Notch). Through mathematical modeling, they identified how this system could create the sharp boundaries observed in differentiation patterns.


Autonomous Synchronization of Chemically Coupled Synthetic Oscillators. Lang M, Marquez-Lago TT, Stelling J, Waldherr S.

Bull Math Biol. 2011 Mar 4. [Epub ahead of print]

Although oscillating systems have been developed through synthetic biology, researchers have not yet developed systems to allow population oscillations in mammalian cells. Lang et al utilized a mathematical construct with ODEs to identify network structures with the best performance in promoting autonomous synchronization. They took into account heterogeneity of the medium and cell density in the formation of phase differences between oscillatory signals in populations. In conclusion, they found that ‘periodical transcription of the protein producing the signaling molecule, but also the receptor protein is necessary to achieve good performance.’

Potentially useful model systems

Delta-Notch

Neuronal Signaling- ability to regulate degradation of neurotransmitter

Hormones

Cancer adhesion

Axonal growth- is this genetically regulated?

Other paracrine signalling systems....

Challenges

Balance of parameters to get oscillation- sensitivity of genetic parameters. Similar to other problems in oscillating systems.

Mechanical construction of the system- Hasty relied on fast reproduction rate of bacteria- not an option in mammalian cells.


Thyroxine Model: Update 5.4.11

Thyroxine (T4) is natively synthesized by the thyroid gland and is secreted into blood plasma. When it enters target cells, it controls gene expression by binding to transcription factors within the nuclei. Thyroxin has been found to be involved in controlling the growth and differentiation of cells.

Fire and degrade mechanism: Static biofilm with cells genetically modified to contain a plasmid with all necessary genetic components.

Promoter for fluorescent protein (GFP) is that which is recognized by Thyroxine. Therefore, in the presence of thyroxine, cells will fluoresce. Thyroxine also induces the production of further thyroxine. The exact mechanisms of synthesis will be explored later due to the complicated interplay between thyroglobin and thyroxine.

Need to figure out degradation/inhibition pathway to temporarily inhibit the effects of thyroxine. Degradation system should be intracellular, exceed the half life of thyroxine.

If we provide a mechanical construct to route thyroxine produced by the terminal band back to the start, can form an infinite loop of longitudinally traveling fluorescence.

Presentation Outline: Update 5.4.11

Introduction

Research goal/proposal - What are we trying to accomplish?

What are some of the underlying principles of mammalian cell-cell communication?

What are the challenges faced in this problem?

What has already been done (cite 2-3 previous studies in depth)? - How have those researchers addressed the previously stated challenges?

Model 1 - Explain how it works, why its cool

Model 2 - Explain how it works, why its cool

Tools/materials needed to develop the system/troubleshooting.

Future applications of the study.

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