Difference between revisions of "CH391L/S13/Genetic Circuits"
(New page: Category:CH391L_S13 ==Introduction== ===History=== The concept of a “genetic circuit” has a long and storied past. When summarizing the conclusions from the 1961 Cold Spring Harbo...)
Revision as of 09:50, 16 April 2013
- 1 Introduction
- 2 Purpose with Perspective: Rising above the ‘noise’
- 3 Circuitry Concepts
- 4 Natural Genetic Circuits
- 5 Synthetic Genetic Circuits
The concept of a “genetic circuit” has a long and storied past. When summarizing the conclusions from the 1961 Cold Spring Harbor Symposium, Francois Jacob and Jacques Monod – of Lac operon fame –established the electronic circuit paradigm for gene regulation. Jacob and Monod stated that different regulatory elements (i.e repressors, activators, etc.) could be assembled into a diversity of ‘circuits’ [Jacob1961]. Here, we see a surprisingly accurate prediction for the developments that form a one of the major thrusts in synthetic biology.
Later, increased computing power was a considerable driving force for modeling gene regulation. Still, a paucity of understood pathways and regulatory elements prevented major gains. This situation changed with the onset of the ‘genomic era’, which was defined by developments like Sanger sequencing and PCR. Armed with new biological ‘parts’, researchers began constructing genetic circuits that experimentally validated mathematical modeling as well as the belief that engineering principles could be applied to biological systems. In the year 2000, a trinity of Nature papers demonstrated synthetic genetic circuitry [Gardner2000] [Elowitz2000] [Becskei2000].
The definition of a genetic circuit is one rather important issue that is often overlooked. Also, it should be noted that there is a difference between ‘natural’ and ‘synthetic’ genetic circuits. The Lac operon is one example of a well-characterized natural genetic circuit. By contrast, the repressilator represents a genetic circuit that was synthesized or assembled from different regulatory elements.
Given the established paradigm, it helps to first consider the electronic circuit. A simple explanation defines an electronic circuit as connected elements or components that permit the flow of electrical current. Typically, that electrical current derives from an external source (i.e. another circuit), which represents an input signal. This circuit functions to interpret or process the input signal and produce a particular output signal or even mechanical actuation.
In general, a genetic circuit is a series of interacting biological components that exert regulatory or signaling function(s). The circuit may also have one or more of the following characteristics listed below
Signal Processing / Signal Transduction Bistability / Multistability Memory Logical Integration
Purpose with Perspective: Rising above the ‘noise’
As with many aspects of synthetic biology, engineering synthetic genetic circuits is a young field. As such, there is both considerable promise and, at times, undue hype. It is wise to consider the utility of increased circuit engineering and its impact upon the two types of genetic circuits: naturally occurring and synthetic.
Understanding natural system // creating new control systems
Natural genetic circuits include a vast array of regulatory networks that ranges from the simple, yet sophisticated Lac operon to complex chromatin remodeling. During the study of these and other naturally occurring regulatory networks, synthetic genetic circuits offer a means for examining the operating principles of regulatory elements or modules from a more complex system [Yokobayashi2002]. Conversely, application-driven efforts seek to create new genetic circuits for pharmaceutical
Despite their differences, both research thrusts employ so-called “top-down” – or decomposition – and “bottom-up” – or synthesis – strategies.
In the study of complex regulatory systems, a top-down approach is employed to identify key elements of a regulatory pathway. However, this approach may yield an incomplete picture or a general lack of depth. In this scenario, bottom-up engineering of simpler synthetic circuits may afford a deeper understanding of the more complex natural system.
Perhaps obvious, de novo circuit engineering favors bottom-up approaches to create regulatory networks with expanded functionality. Still, top-down decomposition
In considering the 1961 Cold Spring Harbor Symposium, it is obvious that study of natural genetic circuits predates the term itself. Efforts to identify and thoroughly characterize natural regulatory mechanisms remain a major area of research. Simple synthetic genetic circuits complement this effort by examining the operating principles of more complex natural systems.
Additionally, there is the application driven bala
Emulation of biology
Emulation of electronics
Problems with instantiation
State and Memory
Natural Genetic Circuits
The E. coli tryptophan (Trp) operon provides an interesting example of genetic regulation through input signal integration. In brief, the Trp operon regulates expression of tryptophan biosynthesis enzymes. In the presence of high tryptophan, Trp operon gene expression is undesirable. While transcriptional silencing depends upon tryptophan levels, two different detection methods are employed.
When the concentration of free tryptophan is high, a tryptophan–activated repressor (trp repressor) will bind to operator sequences blocking transcription by RNA polymerase. Next, a short leader transcript (trpL) detects tryptophanyl-tRNA levels as the coding sequence has two sequential tryptophan codons. Sufficiently high tryptophan levels permit adequate aminoacylation of the tRNATrp and standard translation. After translation termination, the ribosome will dissociate allowing the mRNA to fold into a terminator, which ends transcription. Should tryptophan and tryptophanyl-tRNA levels be low, the ribosome will pause upon encountering the adjacent tryptophan codons. Ribosome stalling leads to formation of an antiterminator that allows the RNA polymerase resume transcription. [Yanofsky2007]
Salmonella Phase Variation
Salmonella has the adaptive ability to switch or toggle between two flagellin genes thereby avoiding detection by the immune system. This so-called phase variation represents a nature example of bistability; the bacteria can exist in one of two ‘states’ [Yamamoto2006]. Interestingly, phase variation employs an inversion-mediated mechanism similar to recently published synthetic logic circuits [Siuti2013] [Bonnet2013].