Utilising datasheets for the informed automated design and build of a synthetic metabolic pathway.

Automation workflow Datasheets Design of Experiment (DoE) Synthetic biology

Journal

Journal of biological engineering
ISSN: 1754-1611
Titre abrégé: J Biol Eng
Pays: England
ID NLM: 101306640

Informations de publication

Date de publication:
2019
Historique:
received: 27 09 2018
accepted: 07 01 2019
entrez: 25 1 2019
pubmed: 25 1 2019
medline: 25 1 2019
Statut: epublish

Résumé

The automation of modular cloning methodologies permits the assembly of many genetic designs. Utilising characterised biological parts aids in the design and redesign of genetic pathways. The characterisation information held on datasheets can be used to determine whether a biological part meets the design requirements. To manage the design of genetic pathways, researchers have turned to modelling-based computer aided design software tools. An automated workflow has been developed for the design and build of heterologous metabolic pathways. In addition, to demonstrate the powers of electronic datasheets we have developed software which can transfer part information from a datasheet to the Design of Experiment software JMP. To this end we were able to use Design of Experiment software to rationally design and test randomised samples from the design space of a lycopene pathway in The use of standardised and characterised biological parts will empower a design-oriented synthetic biology for the forward engineering of heterologous expression systems. A Design of Experiment approach streamlines the design-build-test cycle to achieve optimised solutions in biodesign. Developed automated workflows provide effective transfer of information between characterised information (in the form of datasheets) and DoE software.

Sections du résumé

BACKGROUND BACKGROUND
The automation of modular cloning methodologies permits the assembly of many genetic designs. Utilising characterised biological parts aids in the design and redesign of genetic pathways. The characterisation information held on datasheets can be used to determine whether a biological part meets the design requirements. To manage the design of genetic pathways, researchers have turned to modelling-based computer aided design software tools.
RESULT RESULTS
An automated workflow has been developed for the design and build of heterologous metabolic pathways. In addition, to demonstrate the powers of electronic datasheets we have developed software which can transfer part information from a datasheet to the Design of Experiment software JMP. To this end we were able to use Design of Experiment software to rationally design and test randomised samples from the design space of a lycopene pathway in
CONCLUSION CONCLUSIONS
The use of standardised and characterised biological parts will empower a design-oriented synthetic biology for the forward engineering of heterologous expression systems. A Design of Experiment approach streamlines the design-build-test cycle to achieve optimised solutions in biodesign. Developed automated workflows provide effective transfer of information between characterised information (in the form of datasheets) and DoE software.

Identifiants

pubmed: 30675181
doi: 10.1186/s13036-019-0141-z
pii: 141
pmc: PMC6339355
doi:

Types de publication

Journal Article

Langues

eng

Pagination

8

Subventions

Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/M025632/1
Pays : United Kingdom

Déclaration de conflit d'intérêts

Not applicable.Not applicable.The authors declare that they have no competing interests.Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Références

J Biol Eng. 2011 Sep 20;5:12
pubmed: 21933410
ACS Synth Biol. 2017 Jan 20;6(1):148-158
pubmed: 27490704
Crit Rev Biotechnol. 2018 Aug;38(5):647-656
pubmed: 28954542
Nat Methods. 2014 May;11(5):508-20
pubmed: 24781324
Biotechnol Prog. 2008 Nov-Dec;24(6):1191-203
pubmed: 19194932
PLoS One. 2017 Apr 19;12(4):e0176013
pubmed: 28422998
Metab Eng. 2017 Jul;42:98-108
pubmed: 28602523
Front Bioeng Biotechnol. 2015 Feb 24;3:19
pubmed: 25759811
J Biol Eng. 2013 May 10;7(1):13
pubmed: 23663447
Nat Biotechnol. 2008 Jul;26(7):771-4
pubmed: 18612298
J Biol Eng. 2009 Mar 20;3:4
pubmed: 19298678
Nat Biotechnol. 2000 May;18(5):533-7
pubmed: 10802621
J Integr Bioinform. 2018 Mar 19;15(1):
pubmed: 29549707
ACS Synth Biol. 2015 Jul 17;4(7):781-7
pubmed: 25746445
J Biol Eng. 2009 Oct 29;3:19
pubmed: 19874625
Bioinformatics. 2009 Nov 1;25(21):2848-9
pubmed: 19628507
Cold Spring Harb Perspect Biol. 2017 Apr 3;9(4):
pubmed: 28246188
Nat Rev Mol Cell Biol. 2015 Sep;16(9):568-76
pubmed: 26081612
Asian J Androl. 2018 Sep 7;:
pubmed: 30198495
Mar Drugs. 2014 Sep 17;12(9):4810-32
pubmed: 25233369
Commun Biol. 2018 Jun 8;1:66
pubmed: 30271948
ACS Synth Biol. 2018 Jul 20;7(7):1676-1684
pubmed: 29976056
Biochem Soc Trans. 2016 Jun 15;44(3):687-8
pubmed: 27284027
Nature. 2015 Apr 9;520(7546):141-2
pubmed: 25855435
SLAS Technol. 2019 Jun;24(3):291-297
pubmed: 30165777
Metab Eng. 2018 Jul;48:33-43
pubmed: 29753070
Medicine (Baltimore). 2015 Aug;94(33):e1260
pubmed: 26287411
J Lab Autom. 2016 Feb;21(1):49-56
pubmed: 26163567
FEMS Yeast Res. 2015 Feb;15(1):1-9
pubmed: 24903193
Nat Biotechnol. 2008 Jul;26(7):787-93
pubmed: 18612302
ACS Synth Biol. 2016 Aug 19;5(8):817-26
pubmed: 26854090
Proc Natl Acad Sci U S A. 2011 Jun 28;108(26):10626-31
pubmed: 21670266
Nat Biotechnol. 2003 Jul;21(7):796-802
pubmed: 12778056

Auteurs

Kealan Exley (K)

1Department of Bioengineering, Imperial College London, London, UK.
2Imperial College Centre for Synthetic Biology, Imperial College London, London, UK.

Christopher Robert Reynolds (CR)

1Department of Bioengineering, Imperial College London, London, UK.
2Imperial College Centre for Synthetic Biology, Imperial College London, London, UK.

Lorna Suckling (L)

1Department of Bioengineering, Imperial College London, London, UK.
3The London DNA Foundry, Imperial College London, London, UK.

Soo Mei Chee (SM)

1Department of Bioengineering, Imperial College London, London, UK.
4SynbiCITE, Imperial College London, London, UK.

Argyro Tsipa (A)

1Department of Bioengineering, Imperial College London, London, UK.
4SynbiCITE, Imperial College London, London, UK.

Paul S Freemont (PS)

4SynbiCITE, Imperial College London, London, UK.
5Section of Structural Biology, Department of Medicine, Imperial College London, London, UK.

David McClymont (D)

3The London DNA Foundry, Imperial College London, London, UK.

Richard Ian Kitney (RI)

1Department of Bioengineering, Imperial College London, London, UK.
4SynbiCITE, Imperial College London, London, UK.

Classifications MeSH