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Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks

BACKGROUND: The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic...

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Detalles Bibliográficos
Autores principales: Beal, Jacob, Lu, Ting, Weiss, Ron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3151252/
https://www.ncbi.nlm.nih.gov/pubmed/21850228
http://dx.doi.org/10.1371/journal.pone.0022490
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author Beal, Jacob
Lu, Ting
Weiss, Ron
author_facet Beal, Jacob
Lu, Ting
Weiss, Ron
author_sort Beal, Jacob
collection PubMed
description BACKGROUND: The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. METHODOLOGY/PRINCIPAL FINDINGS: To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes ([Image: see text]) and latency of the optimized engineered gene networks. CONCLUSIONS/SIGNIFICANCE: Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems.
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spelling pubmed-31512522011-08-17 Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks Beal, Jacob Lu, Ting Weiss, Ron PLoS One Research Article BACKGROUND: The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. METHODOLOGY/PRINCIPAL FINDINGS: To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes ([Image: see text]) and latency of the optimized engineered gene networks. CONCLUSIONS/SIGNIFICANCE: Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems. Public Library of Science 2011-08-05 /pmc/articles/PMC3151252/ /pubmed/21850228 http://dx.doi.org/10.1371/journal.pone.0022490 Text en Beal et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Beal, Jacob
Lu, Ting
Weiss, Ron
Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks
title Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks
title_full Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks
title_fullStr Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks
title_full_unstemmed Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks
title_short Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks
title_sort automatic compilation from high-level biologically-oriented programming language to genetic regulatory networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3151252/
https://www.ncbi.nlm.nih.gov/pubmed/21850228
http://dx.doi.org/10.1371/journal.pone.0022490
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