Computer Logic in Microbial Systems

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Introduction

Figure 1. An example of applied genetic programming is the designof Yersinia pseudotuberculosis that specifically target cancer cells[1].


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 (Brophy and Voigt, 2014). 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 [2]. Applications like this could be used to create synthetic organisms capable of accomplishing highly specific tasks such as targeting specific tissues or compounds.


Section 1

Figure 2. Examples of logic gates constructed in bacteria[3].

Include some current research, with at least one figure showing data.

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Section 2

Include some current research, with at least one figure showing data.

Section 3

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Section 4

Conclusion

References

  1. ↑ Anderson 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. ↑ Anderson 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.
  3. ↑ Brophy JAN, Voigt CA. Principles of Genetic Circuit Design. (2014). Nature Methods 11(5): 508 – 520. DOI:10.1038/NMETH.2926.



Authored for BIOL 238 Microbiology, taught by Joan Slonczewski, 2017, Kenyon College.

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