Computer Logic in Microbial Systems: Difference between revisions
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==Construction of Complex Logic== | ==Construction of Complex Logic== | ||
[[Image:multicell.png|thumb|300px| | [[Image:multicell.png|thumb|300px|left|<b>Figure 5.</b>. <ref name = Tamsir2011/>]] | ||
[[Image:complexlogic.png|thumb|300px|right|<b>Figure6.</b>. <ref name = Tamsir2011/>]] | |||
==Section 4== | ==Section 4== | ||
Revision as of 00:35, 21 April 2017
Introduction
By Jeremy Moore
Synthetic biology is a quickly evolving field that fuses biological and chemical science with engineering principles. One major task for synthetic biologists is harnessing cell’s innate ability to perform tightly concerted metabolic processes in order to produce molecules of industrial and medical relevance. In other words, one goal of synthetic biology is to create a programming language for cellular processes that can be altered in deterministic ways to generate specific products. Applying computer logic to living systems is challenging, as gene regulation is highly sensitive to the environment and requires a tightly controlled balance of regulatory factors[2]. Nonetheless, several methods have been developed to translate logical operators into genetic circuits.
Programmable cells have myriad applications to industry and medicine. As an example, a strain of Yersinia pseudotuberculosis was modified to invade cancerous cells in response to environmental conditions [1]. Applications like this could be used to create synthetic organisms capable of accomplishing highly specific tasks such as targeting specific tissues or compounds.
Logic Gates in Biological Context
The central principle to logic gate construction in living systems, is linking an output, such as expression of a fluorophore, to the expression of other genes [2]. For example, to get an OR logic gate (where one of two or more stimuli both activate a response), one could construct a system where two different promoters both activate a gene. Similarly, a NOR gate (where either response prevents a response) could be constructed as in Figure 1a, where expression of a repressor is controlled by two adjacent promoters. This repressor then prevents an output [2]. Gates that use AND logic can also be constructed. One method of AND gate construction is to have an output activated by a protein that requires a chaperone[2]. Thus, both the activator and chaperone must be transcribed to induce expression of the output.
The left side of Figure 2 shows several examples of possible logic gate designs[2]. In these examples, the output is some fluorophore, the expression of which is dependent on some interaction between two other promoters and the genes they serve. The right side of Figure 2 displays predicted expression of the fluorophore given expression of the two promoters that build the logical operation.
Counting and Memory Function Using Invertases
Counters are important components of digital circuits and computer programs, so translating their function into living systems is necessary before implementing more complex computational functions. A creative method of counting events was described by Friedland et al.. As shown in Figure 3, creating a line of several invertible DNA elements next to each other allows for the construction of near-digital circuits[4]. In each element is an invertase enzyme that inverts the elements upon activation of an upstream promoter. This inversion then places a promoter in front of the next element in the sequence.
Being able to count the number of times a particular eent has occured allows you to decide exactly when a particular response occurs. One could, for example, tie the inversion events to cell division [2]. Thus, the number of adjacent invertible sequences would decide exactly how many times a particular strain can divide before terminating. In medical applications of genetic circuit design, this alleviates some of the safety concern of using bacteria to treat other infections [4].
Construction of Complex Logic
Section 4
Conclusion
References
- ↑ 1.0 1.1 JC, Clarke EJ, Arkin AP, Voigt CA. Environmentally Controlled Invasion of Cancer Cells by Engineered Bacteria. (2006). JMB 355: 619 – 627. doi:10.1016/j.jmp.2005.10.076.
- ↑ 2.0 2.1 2.2 2.3 2.4 2.5 2.6 Brophy JAN, Voigt CA. Principles of Genetic Circuit Design. (2014). Nature Methods 11(5): 508 – 520. DOI:10.1038/NMETH.2926.
- ↑ 3.0 3.1 3.2 http://www.nature.com/nature/journal/v469/n7329/abs/nature09565.html Tamsir A, Tabor JJ, Voigt CA. Robust multicellular computing using genetically encoded NOR gates and chemical ‘wires’. (2011) Nature 469: 212 – 215. doi:10.1038/nature09565.
- ↑ 4.0 4.1 4.2 . Friedland AE, Lu TK, Wang X, Shi D, Church G, Collins JJ. Synthetic Gene Networks that Count. (2009). Science 324(5931): 1199 – 1202.
Authored for BIOL 238 Microbiology, taught by Joan Slonczewski, 2017, Kenyon College.
