CHE.496/2008/Responses/a13

Systems biology and synthetic biology

 * Discussion leader: George Washington (Discussion guide)

Kevin Hershey's Response

 * Systems biology as a foundation for genome-scale synthetic biology
 * The article by Barrett et al. describes the transition from systems biology to synthetic biology. It describes some of the advances in mathematical understanding of biology, in silico analysis, and how synthetic biology can use these tools. It goes on to discuss software applications to synthetic biology, and how they can be used. It finishes by discussing system biology’s importance in successfully using natural evolution. Natural evolution, combined with synthetic biology’s ability to produce constructs based on mathematical understanding, can be a very powerful tool.
 * Modular approaches to expanding the functions of living matter
 * The review by Chin provides even further analysis of Ellowitz’s repressilator and Weiss’s ‘bullseye’ cell configuration discussed earlier in the course. The article then goes on to discuss Smolke’s system to create the caffeine sensing bacteria discussed earlier in the course. However, a new aspect of synthetic biology is described by Chin’s and Rackham’s manipulation of the ribosome itself. This is novel, because many of the mechanisms studied in this class dealt with the post-transcriptional RNA, rather than the actual machinery. The modified ribosomes allow for new functions.
 * KPHershey 12:05, 1 April 2008 (EDT)

Patrick Gildea's Response

 * Systems biology as a foundation for genome-scale synthetic biology
 * The purpose of this article is to make connections between the fields of systems biology and synthetic biology, especially with respect to genome engineering. Figure 1 in the article sums up the relationships between systems biology and synthetic biology. An important point that is made in the paper is the use of computer modeling of cellular systems – especially metabolic pathways. This is a very useful tool but requires knowledge of the kinetics and fluxes in a metabolic system, which can be hard to characterize. But this can be done via analysis of molecular components in the various cellular systems. This paper is beneficial in the metabolic engineering aspect by discussing the different aspects of modeling and how that modeling can be brought along by systems biology.
 * Modular approaches to expanding the functions of living matter
 * The article discusses the complexities and important factors that must be considered in developing complex biological networks. Programming biological networks have been aided by the use of modules – both natural and unnatural based modules. Examples of the natural (toggle switch, etc) and unnatural modules (cascades, etc.) are given in the paper. However, I am concerned about the “overuse” of these modules. Biological modules are not as convenient as transistors, resistors, etc. if we tie in a lot of modules that have different functions but similar promoters, won’t the inducer from one module mix in with other modules and cause a chain reaction of entropy? Case in point: my DuoRepressilator would never function correctly if the repressor genes from one repressilator were similar to the other repressilator let alone the toggle switch. The article does discuss stochasticity and provides a solution – transcription factors that negatively regulates its own expression. I am not sure I understand this thoroughly and I don’t see how this can avoid errors that occur when chemical inducers from different modules mix together to cause unknown results.
 * Patrick Gildea 16:43, 1 April 2008 (EDT):

Eyad Lababidi's Response

 * Systems biology as a foundation for genome-scale synthetic biology
 * This article talks a bit about defining the different biological fields because they all apparently have different niches, but the main point of the article was about modeling cell functions and metabolic processes with boolean math. This is quite amazing when the equation can be written without the metabolic rates. This would allow for implementing on silicon and allows for better modeling and prediction. This seems like aneat idea, but id really like to see an example of it because as far as i saw the article didnt really show how the idea worked.
 * Modular approaches to expanding the functions of living matter
 * Chin intros by talking about the methods synthetic biologists have been using, how functions can be added from other organism or novel functions can be added. He argues that novel metabolic pathways are very difficult to insert because of the complexities of workign with a live cell with many metabolic functions going on, but inorder to take advantage of what synthetic biology has to offer novel function are the way to go. Chin also talk about why synthetic biology is important and goes on in the body of the article to really go into a variety of different projects that exemplify the power of synthetic biology. I really thought many of those examples could be useful to our project to use as a part, this does increase complexity but it would really show the modularity of the parts we'll be using.
 * Eyad Lababidi 01:56, 2 April 2008 (EDT)

George McArthur's Response

 * Systems biology as a foundation for genome-scale synthetic biology
 * Palsson and friends make a strong case for the yin-yang nature of systems and synthetic biology. Just as new knowledge in systems biology can be utilized by synthetic biologists in designing and constructing biological systems, systems biologists can test their theories using synthetic biology by building systems from the ground up.  As Feynman is famously quoted, "what I cannot create, I do not understand."  The most important thing to get from this article, I think, is the fact that characterization is critical to both systems and synthetic biology (i.e., characterization is needed for not only design and construction, but also modeling).  Moreover, directed evolution can serve as a powerful tool to finely tune synthetic parts.
 * Modular approaches to expanding the functions of living matter
 * In this article Chin discusses the challenge of adding new, specific functions to living organisms. Although there has been some success in constructing simple unnatural devices/systems/networks in cells, increasingly complex synthetic systems will require new strategies that include "spatial and temporal control of molecular interactions and fluxes to achieve the desired outcomes."  Summaries of work that has already been done is provided in the paper, which will serve as a great resource during the summer.  However, the most valuable part of the paper for the team, perhaps, may be the discussion of 'future directions'.  In particular, interfacing is a major concern when dealing with complex systems made of several modules.  Therefore, standardization of modules is necessary for impedance matching between modules.  Furthermore, methods for adjusting cell metabolism so as to obtain flux balance and/or endowing cells with the ability to enter a quiescent state provide solutions for more complex systems.
 * GMcArthurIV 16:44, 2 April 2008 (EDT)

Dan Tarjan's Response
Daniel R Tarjan 17:21, 2 April 2008 (EDT)
 * Systems biology as a foundation for genome-scale synthetic biology
 * Systems biology will deliver the information and modeling tools we need to be able to successfully engineer synthetic biological systems - or at least that's what this article posits. Automated data collection methods have come about with technological advances but not all aspects of a cell's state can yet be measure this way. (Especially the myriad molecular concentrations of interesting substances). Furthermore while we are gaining maps of various systems of interaction (protein-protein, gene circuits, etc) we don't yet know the parameters that are associated with these interactions. What inputs systems need, stoichiometric coefficients and so on. I think they mention some ways that this limitation can be worked around - not entirely sure. Of interest for the team I think are the OptStrain pathway engineering guideline and perhaps citation 13 about the current modeling tools.
 * Modular approaches to expanding the functions of living matter
 * As mentioned in the other article, our current modeling techniques - they mention deterministic modeling specifically - have limitations, see above. The article then discusses two angles from which to approach synbio: 'remixing' natural biological systems, and making unnatural systems/components thereof. While the former relies mainly on the rearrangement of existing pathways and the transcriptional wiring that connects them (which we've discusseda good bit), the later talks about modifying the base structures that make biological systems. Expanded sets of amino acids allow novel interactions in the molecular realm/with genetic material: "photo-cross-linkers, chemical handles, heavy atoms, redox sensors, post-translational modiﬁcations and ﬂuorophores." RNA aptamers are again mentioned as being a valuable regulatory tools with their mRNA binding abilities. Orthogonal sets of cellular machinery allow for non-interacting processes to avoid interference with and by natural cellular processes. These are all tools we should consider when faced with engineering challenges this summer.