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dc.contributor.authorBanks, AM
dc.contributor.authorWhitfield, CJ
dc.contributor.authorBrown, SR
dc.contributor.authorFulton, DA
dc.contributor.authorGoodchild, SA
dc.contributor.authorGrant, C
dc.contributor.authorLove, J
dc.contributor.authorLendrem, DW
dc.contributor.authorFieldsend, JE
dc.contributor.authorHoward, TP
dc.date.accessioned2023-04-25T09:28:15Z
dc.date.issued2021-12-13
dc.date.updated2023-04-25T07:07:47Z
dc.description.abstractCell-free protein synthesis (CFPS) reactions have grown in popularity with particular interest in applications such as gene construct prototyping, biosensor technologies and the production of proteins with novel chemistry. Work has frequently focussed on optimising CFPS protocols for improving protein yield, reducing cost, or developing streamlined production protocols. Here we describe a statistical Design of Experiments analysis of 20 components of a popular CFPS reaction buffer. We simultaneously identify factors and factor interactions that impact on protein yield, rate of reaction, lag time and reaction longevity. This systematic experimental approach enables the creation of a statistical model capturing multiple behaviours of CFPS reactions in response to components and their interactions. We show that a novel reaction buffer outperforms the reference reaction by 400% and importantly reduces failures in CFPS across batches of cell lysates, strains of E. coli, and in the synthesis of different proteins. Detailed and quantitative understanding of how reaction components affect kinetic responses and robustness is imperative for future deployment of cell-free technologies.en_GB
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)en_GB
dc.format.extent218-229
dc.format.mediumElectronic-eCollection
dc.identifier.citationVol. 20, pp. 218-229en_GB
dc.identifier.doihttps://doi.org/10.1016/j.csbj.2021.12.013
dc.identifier.grantnumberEP/N026683/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/133007
dc.identifierORCID: 0000-0003-0340-7431 (Love, John)
dc.identifierScopusID: 7202207902 (Love, John)
dc.identifierORCID: 0000-0002-0683-2583 (Fieldsend, Jonathan E)
dc.language.isoenen_GB
dc.publisherElsevier / Research Network of Computational and Structural Biotechnologyen_GB
dc.relation.urlhttps://www.ncbi.nlm.nih.gov/pubmed/35024094en_GB
dc.relation.urlhttps://doi.org/10.25405/data.ncl.17041931en_GB
dc.rights© 2021 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectAutomationen_GB
dc.subjectCell-free protein synthesis (CFPS)en_GB
dc.subjectDesign of Experiments (DoE)en_GB
dc.subjectRobustnessen_GB
dc.subjectStatistical engineeringen_GB
dc.titleKey reaction components affect the kinetics and performance robustness of cell-free protein synthesis reactionsen_GB
dc.typeArticleen_GB
dc.date.available2023-04-25T09:28:15Z
dc.identifier.issn2001-0370
exeter.place-of-publicationNetherlands
dc.descriptionThis is the final version. Available on open access from Elsevier via the DOI in this recorden_GB
dc.descriptionData statement: All data are available both in Source Data files associated with this publication, and at https://doi.org/10.25405/data.ncl.17041931en_GB
dc.identifier.eissn2001-0370
dc.identifier.journalComputational and Structural Biotechnology Journalen_GB
dc.relation.ispartofComput Struct Biotechnol J, 20
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2021-12-08
dc.rights.licenseCC BY
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2021-12-13
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2023-04-25T09:25:50Z
refterms.versionFCDVoR
refterms.dateFOA2023-04-25T09:28:19Z
refterms.panelAen_GB


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© 2021 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2021 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).