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Design and assembly of DNA molecules using multi-objective optimization

Rapid engineering of biological systems is currently hindered by limited integration of manufacturing constraints into the design process, ultimately reducing the yield of many synthetic biology workflows. Here we tackle DNA engineering as a multi-objective optimization problem aiming at finding the...

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Detalles Bibliográficos
Autores principales: Gaeta, Angelo, Zulkower, Valentin, Stracquadanio, Giovanni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8524653/
https://www.ncbi.nlm.nih.gov/pubmed/34676304
http://dx.doi.org/10.1093/synbio/ysab026
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author Gaeta, Angelo
Zulkower, Valentin
Stracquadanio, Giovanni
author_facet Gaeta, Angelo
Zulkower, Valentin
Stracquadanio, Giovanni
author_sort Gaeta, Angelo
collection PubMed
description Rapid engineering of biological systems is currently hindered by limited integration of manufacturing constraints into the design process, ultimately reducing the yield of many synthetic biology workflows. Here we tackle DNA engineering as a multi-objective optimization problem aiming at finding the best tradeoff between design requirements and manufacturing constraints. We developed a new open-source algorithm for DNA engineering, called Multi-Objective Optimisation algorithm for DNA Design and Assembly, available as a Python and Anaconda package, as well as a Docker image. Experimental results show that our method provides near-optimal constructs and scales linearly with design complexity, effectively paving the way to rational engineering of DNA molecules from genes to genomes.
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spelling pubmed-85246532021-10-20 Design and assembly of DNA molecules using multi-objective optimization Gaeta, Angelo Zulkower, Valentin Stracquadanio, Giovanni Synth Biol (Oxf) Research Article Rapid engineering of biological systems is currently hindered by limited integration of manufacturing constraints into the design process, ultimately reducing the yield of many synthetic biology workflows. Here we tackle DNA engineering as a multi-objective optimization problem aiming at finding the best tradeoff between design requirements and manufacturing constraints. We developed a new open-source algorithm for DNA engineering, called Multi-Objective Optimisation algorithm for DNA Design and Assembly, available as a Python and Anaconda package, as well as a Docker image. Experimental results show that our method provides near-optimal constructs and scales linearly with design complexity, effectively paving the way to rational engineering of DNA molecules from genes to genomes. Oxford University Press 2021-10-11 /pmc/articles/PMC8524653/ /pubmed/34676304 http://dx.doi.org/10.1093/synbio/ysab026 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Gaeta, Angelo
Zulkower, Valentin
Stracquadanio, Giovanni
Design and assembly of DNA molecules using multi-objective optimization
title Design and assembly of DNA molecules using multi-objective optimization
title_full Design and assembly of DNA molecules using multi-objective optimization
title_fullStr Design and assembly of DNA molecules using multi-objective optimization
title_full_unstemmed Design and assembly of DNA molecules using multi-objective optimization
title_short Design and assembly of DNA molecules using multi-objective optimization
title_sort design and assembly of dna molecules using multi-objective optimization
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8524653/
https://www.ncbi.nlm.nih.gov/pubmed/34676304
http://dx.doi.org/10.1093/synbio/ysab026
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