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Synthetic biology is the process of forward engineering living systems. These systems can be used to produce biobased materials, agriculture, medicine, and energy. One approach to designing these systems is to employ techniques from the design of embedded electronics. These techniques include abstraction, standards, modularity, automated design, and formal semantic models of computation. Together, these elements form the foundation of “biodesign automation,” where software, robotics, and microfluidic devices combine to create exciting biological systems of the future. This paper describes a “hardware, software, wetware” codesign vision where software tools can be made to act as “genetic compilers” that transform high-level specifications into engineered “genetic circuits” (wetware). This is followed by a process where automation equipment, well-defined experimental workflows, and microfluidic devices are explicitly designed to house, execute, and test these circuits (hardware). These systems can be used as either massively parallel experimental platforms or distributed bioremediation and biosensing devices. Next, scheduling and control algorithms (software) manage these systems’ actual execution and data analysis tasks. A distinguishing feature of this approach is how all three of these aspects (hardware, software, and wetware) may be derived from the same basic specification in parallel and generated to fulfill specific cost, performance, and structural requirements.
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Engineering Genetic Circuits: Advancements in Genetic Design Automation Tools and Standards for Synthetic Biology
Synthetic biology is a field at the intersection of biology and engineering. Inspired by engineering principles, researchers use defined parts to build functionally defined biological circuits. Genetic design automation allows scientists to design, model, and analyze their genetic circuits in silico before building them in the lab, saving time and resources in the process. Establishing synthetic biology’s future is dependent on genetic design automation, since the computational approach opens the field to a broad, interdisciplinary community. However, challenges with part libraries, standards, and software tools are currently stalling progress in the field. This review first covers re- cent advancements in genetic design automation, followed by an assessment of the challenges ahead, and a proposed automated genetic design workflow for the future.
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- Award ID(s):
- 1856740
- PAR ID:
- 10332810
- Editor(s):
- Takano, Eriko; Breitling, Rainer
- Date Published:
- Journal Name:
- Current opinion in microbiology
- Volume:
- 68
- ISSN:
- 1369-5274
- Page Range / eLocation ID:
- 102155
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.mib.2022.102155
