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Scaling up genetic circuit design for cellular computing: advances and prospects
Synthetic biology aims to engineer and redesign biological systems for useful real-world applications in biomanufacturing, biosensing and biotherapy following a typical design-build-test cycle. Inspired from computer science and electronics, synthetic gene circuits have been designed to exhibit cont...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6244767/ https://www.ncbi.nlm.nih.gov/pubmed/30524216 http://dx.doi.org/10.1007/s11047-018-9715-9 |
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author | Xiang, Yiyu Dalchau, Neil Wang, Baojun |
author_facet | Xiang, Yiyu Dalchau, Neil Wang, Baojun |
author_sort | Xiang, Yiyu |
collection | PubMed |
description | Synthetic biology aims to engineer and redesign biological systems for useful real-world applications in biomanufacturing, biosensing and biotherapy following a typical design-build-test cycle. Inspired from computer science and electronics, synthetic gene circuits have been designed to exhibit control over the flow of information in biological systems. Two types are Boolean logic inspired TRUE or FALSE digital logic and graded analog computation. Key principles for gene circuit engineering include modularity, orthogonality, predictability and reliability. Initial circuits in the field were small and hampered by a lack of modular and orthogonal components, however in recent years the library of available parts has increased vastly. New tools for high throughput DNA assembly and characterization have been developed enabling rapid prototyping, systematic in situ characterization, as well as automated design and assembly of circuits. Recently implemented computing paradigms in circuit memory and distributed computing using cell consortia will also be discussed. Finally, we will examine existing challenges in building predictable large-scale circuits including modularity, context dependency and metabolic burden as well as tools and methods used to resolve them. These new trends and techniques have the potential to accelerate design of larger gene circuits and result in an increase in our basic understanding of circuit and host behaviour. |
format | Online Article Text |
id | pubmed-6244767 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-62447672018-12-04 Scaling up genetic circuit design for cellular computing: advances and prospects Xiang, Yiyu Dalchau, Neil Wang, Baojun Nat Comput Article Synthetic biology aims to engineer and redesign biological systems for useful real-world applications in biomanufacturing, biosensing and biotherapy following a typical design-build-test cycle. Inspired from computer science and electronics, synthetic gene circuits have been designed to exhibit control over the flow of information in biological systems. Two types are Boolean logic inspired TRUE or FALSE digital logic and graded analog computation. Key principles for gene circuit engineering include modularity, orthogonality, predictability and reliability. Initial circuits in the field were small and hampered by a lack of modular and orthogonal components, however in recent years the library of available parts has increased vastly. New tools for high throughput DNA assembly and characterization have been developed enabling rapid prototyping, systematic in situ characterization, as well as automated design and assembly of circuits. Recently implemented computing paradigms in circuit memory and distributed computing using cell consortia will also be discussed. Finally, we will examine existing challenges in building predictable large-scale circuits including modularity, context dependency and metabolic burden as well as tools and methods used to resolve them. These new trends and techniques have the potential to accelerate design of larger gene circuits and result in an increase in our basic understanding of circuit and host behaviour. Springer Netherlands 2018-10-05 2018 /pmc/articles/PMC6244767/ /pubmed/30524216 http://dx.doi.org/10.1007/s11047-018-9715-9 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Xiang, Yiyu Dalchau, Neil Wang, Baojun Scaling up genetic circuit design for cellular computing: advances and prospects |
title | Scaling up genetic circuit design for cellular computing: advances and prospects |
title_full | Scaling up genetic circuit design for cellular computing: advances and prospects |
title_fullStr | Scaling up genetic circuit design for cellular computing: advances and prospects |
title_full_unstemmed | Scaling up genetic circuit design for cellular computing: advances and prospects |
title_short | Scaling up genetic circuit design for cellular computing: advances and prospects |
title_sort | scaling up genetic circuit design for cellular computing: advances and prospects |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6244767/ https://www.ncbi.nlm.nih.gov/pubmed/30524216 http://dx.doi.org/10.1007/s11047-018-9715-9 |
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