CHE.496/2008/Responses/a14

Biological networks

• Discussion leader: Eyad Lababidi (Discussion guide)

Kevin Hershey's Response

• Biological Networks
  • The review by Arkin and Alm discusses the development of systems using gene interactions in biological systems. It discusses how this is possible through high-throughput genetic sequencing techniques. It then goes on to discuss biological networks, and the modules and motifs which compose it. Alm and Arkin define modules as discrete units of function separable from the whole and motifs are the arrangement of specific molecular functions to do something useful. These networks can then be engineered, using synthetic biology practices, but multiple networks tends to complicate things with interference.
• Programming and Engineering Biological Networks
  • This article is very similar to the Chin article for 4/2/2008. In this article, Chin begins by discussing a mammalian toggle switch. Then, he moves onto yet another explanation of Ron Weiss’s ‘bullseye’ configuration. He then finishes by discussing post-translational control and orthogonal ribosomes, as he did in the article Modular Approaches to Expanding the Functions of Living Matter.
• KPHershey 12:26, 2 April 2008 (EDT)

Patrick Gildea's Response

• Biological Networks
  • The focus of this paper is on a more general view of biological networks than Chin’s paper. An important point made in the paper is that biological networks are similar to other complex networks – in which we can use our understanding of complex networks such as hierarchal networks (i.e. the internet) to lend increased understanding of the modus operandi of biological networks – especially metabolic pathways. As before in other papers related to biological networks, modules are brought up; but motifs are described in far more depth with applications mentioned. The paper ends by adding that computer modeling of biological networks is an important step to be made in elucidating and predicting their behavior.
• Programming and Engineering Biological Networks
  • The purpose of this article is to describe different biological networks that have already been developed. Notably the toggle switch in mammalian cells, among others such as pattern-forming circuits (the bulls-eye) and synthetic riboregulator. One of the interesting points brought up in the paper is the use of post-transcriptional control of gene expression utilizing synthetic RNA’s. There is the way of using natural transcription factors (we have read about this in the previous paper for systems biology. Furthermore, Smolke’s antisense agents are another interesting tool for gene expression, too.
• Patrick Gildea 17:44, 2 April 2008 (EDT):

George McArthur's Response

• Biological Networks
  • As we learn more about complex biological interactions (via high-throughput analyses), we are beginning to understand the systems-level workings of the cell. A complete picture of what's going on inside the cell can only be obtained by integrating tons of data from various measurements/analyses, which is why systems biology is critical to the development of synthetic biology. The more we know about how all the parts of a cell work together, the easier it will be to construct our own systems. In addition, like we read before, constructing synthetic biological systems allow researchers to test biological hypotheses generated by systems biology. New and more powerful experimental techniques are needed to determine the character (i.e., parameters) of the molecular interactions that occur within the cell. New insights into natural biology will lead into new ways of approaching synthetic biology. For example, synthetic biology is currently limited to constructing simple genetic circuits and metabolic pathways, but in the future it should be possible to build entire networks that interface with the natural biochemical infrastructure of the cell (including protein, DNA, RNA, and metabolite interactions) and even entire genomes to construct artifical life (i.e., genome engineering). The modularity found in natural biological systems serves as a model for synthetic biology approaches such as the BioBricks initiative, which the iGEM competition is build upon.
• Programming and Engineering Biological Networks
  • Chin reviews recent developments in the field, which we have already talked about in detail. What's most useful to the 2008 VGEM Team is to be aware of the issues Chin points out in his conclusions. The issues relate to the continued technical development of synthetic biology. First, there needs to be better ways to integrate synthetic circuits with cellular physiology (this may be a matter of data-collecting and modeling). Second, the "increased understanding of stochastic effects on organism function should make engineering biology more tractable." Third, DNA-synthesis technology (including error-correction) will make synthesis commonplace so that physical DNA need not be kept in freezers anymore (rather, DNA will be stored electronically as eDNA). Fourth, increased metabolic burden made by larger synthetic circuits/networks need to be addressed (this may be a matter of knocking out pathways or totally re-engineering cellular biochemistry). Fifth, components should be made specific enough so that there is no significant cross-talk so that independent function is ensured (this may be a matter of creating a lot of well-characterized components from which networks could be built or, perhaps, finding some way to isolate/insulate signals within the cell).
• GMcArthurIV 23:16, 8 April 2008 (EDT):

George Washington's Response

• Biological Networks
  • This seemed a very different article from many of the ones we've read. Instead of focusing on any specific biological function, Alm and Arkin approach biological systems as just one special case of networks in general. They are able to demonstrate some neat things about biological networks, such as the fact that they seem to be scale-free, with some nodes (chemical species) having very high connectivity (many reactions) relative to the rest of the network. Properties such as these imply certain analyses that can be performed on the system. For instance, the network approach can directly reproduce modularity in these systems, wherein clusters of chemical species are closely interrelated, only interacting loosely and in very specific ways with other clusters. Unfortunately, I really don't see any direct application of the tools presented in this article to either of our goal projects, as this analysis is far too high level. However, the article was somewhat interesting, and these kinds of tools will certainly be invaluable in any kind of real genome engineering and analysis.
• Programming and Engineering Biological Networks
  • This second of Chin's articles that we've read recently covered much of the same material as the last one. It described the toggle switches, cell-cell communication, post-transcriptional repression, and synthetic ribosomes we've read about before, with some additional details on a few. I'm not certain if or how we should apply any of these to our present ideas - toggle switches are higher level than the terminator and likely unnecessary in metabolic engineering - similarly for the rest. This was an interesting review article, but it was pretty much entirely review.
• George Washington 16:22, 9 April 2008 (EDT)