Automated Conditional Screening of Multiple Escherichia coli Strains in Parallel Adaptive Fed-Batch Cultivations
dc.contributor.author | Hans, Sebastian | |
dc.contributor.author | Haby, Benjamin | |
dc.contributor.author | Krausch, Niels | |
dc.contributor.author | Barz, Tilman | |
dc.contributor.author | Neubauer, Peter | |
dc.contributor.author | Cruz-Bournazou, Mariano Nicolas | |
dc.date.accessioned | 2020-12-28T13:04:15Z | |
dc.date.available | 2020-12-28T13:04:15Z | |
dc.date.issued | 2020-11-11 | |
dc.date.updated | 2020-12-18T14:02:23Z | |
dc.description.abstract | In bioprocess development, the host and the genetic construct for a new biomanufacturing process are selected in the early developmental stages. This decision, made at the screening scale with very limited information about the performance in larger reactors, has a major influence on the efficiency of the final process. To overcome this, scale-down approaches during screenings that show the real cell factory performance at industrial-like conditions are essential. We present a fully automated robotic facility with 24 parallel mini-bioreactors that is operated by a model-based adaptive input design framework for the characterization of clone libraries under scale-down conditions. The cultivation operation strategies are computed and continuously refined based on a macro-kinetic growth model that is continuously re-fitted to the available experimental data. The added value of the approach is demonstrated with 24 parallel fed-batch cultivations in a mini-bioreactor system with eight different Escherichia coli strains in triplicate. The 24 fed-batch cultivations were run under the desired conditions, generating sufficient information to define the fastest-growing strain in an environment with oscillating glucose concentrations similar to industrial-scale bioreactors. | en |
dc.description.sponsorship | BMBF, 031L0018A, ERASysAPP2 - Verbundprojekt: LEANPROT - Entwicklung einer Systembiologie-Plattform für die Entwicklung von lean-proteome-Escherichia coli-Stämmen - Deutsches Teilprojekt A | en |
dc.description.sponsorship | TU Berlin, Open-Access-Mittel – 2020 | en |
dc.identifier.eissn | 2306-5354 | |
dc.identifier.uri | https://depositonce.tu-berlin.de/handle/11303/12257 | |
dc.identifier.uri | http://dx.doi.org/10.14279/depositonce-11133 | |
dc.language.iso | en | en |
dc.relation.ispartof | 10.14279/depositonce-12144 | en |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en |
dc.subject.ddc | 570 Biowissenschaften; Biologie | de |
dc.subject.other | high-throughput screening | en |
dc.subject.other | rapid phenotyping | en |
dc.subject.other | model-based experimental design | en |
dc.subject.other | Escherichia coli | en |
dc.subject.other | automated bioprocess development | en |
dc.title | Automated Conditional Screening of Multiple Escherichia coli Strains in Parallel Adaptive Fed-Batch Cultivations | en |
dc.type | Article | en |
dc.type.version | publishedVersion | en |
dcterms.bibliographicCitation.articlenumber | 145 | en |
dcterms.bibliographicCitation.doi | 10.3390/bioengineering7040145 | en |
dcterms.bibliographicCitation.issue | 4 | en |
dcterms.bibliographicCitation.journaltitle | Bioengineering | en |
dcterms.bibliographicCitation.originalpublishername | MDPI | en |
dcterms.bibliographicCitation.originalpublisherplace | Basel | en |
dcterms.bibliographicCitation.volume | 7 | en |
tub.accessrights.dnb | free | en |
tub.affiliation | Fak. 3 Prozesswissenschaften::Inst. Biotechnologie::FG Bioverfahrenstechnik | de |
tub.affiliation.faculty | Fak. 3 Prozesswissenschaften | de |
tub.affiliation.group | FG Bioverfahrenstechnik | de |
tub.affiliation.institute | Inst. Biotechnologie | de |
tub.publisher.universityorinstitution | Technische Universität Berlin | en |