Raw data for: The knowledge driven DBTL cycle provides mechanistic insights while optimising dopamine production in Escherichia coli

DOI

Dopamine is a promising organic compound with several key applications in emergency medicine, diagnosis and treatment of cancer, production of lithium anodes, and wastewater treatment. Since studies on in vivo dopamine production are limited, this study demonstrates the development and optimisation of a dopamine production strain by the help of the knowledge driven design-build-test-learn (DBTL) cycle for rational strain engineering. The knowledge driven DBTL cycle, involving upstream in vitro investigation, is an automated workflow that enables both mechanistic understanding and efficient DBTL cycling. Following the in vitro cell lysate studies, the results were translated to the in vivo environment through ribosome binding site (RBS) engineering. As a result, we developed a dopamine production strain capable of producing dopamine at concentrations of 69.03 ± 1.2 mg/L which equals 34.34 ± 0.59 mg/gbiomass. Compared to state-of-the-art in vivo dopamine production, our approach improved performance by 2.6 and 6.6-fold, respectively. The fine-tuning of the dopamine pathway by RBS engineering clearly demonstrated the impact of GC content in the Shine-Dalgarno sequence on the RBS strength. In essence, a highly efficient dopamine production strain was developed by implementing the knowledge driven DBTL cycle.

Identifier
DOI https://doi.org/10.18419/DARUS-4714
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/DARUS-4714
Provenance
Creator Hägele, Lorena ORCID logo; Takors, Ralf ORCID logo
Publisher DaRUS
Contributor Hägele, Lorena; Takors, Ralf
Publication Year 2025
Funding Reference DFG 445760252
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact Hägele, Lorena (University of Stuttgart); Takors, Ralf (University of Stuttgart)
Representation
Resource Type Dataset
Format application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
Size 328971; 78321; 46710; 2471462; 73180; 1484201
Version 1.0
Discipline Basic Biological and Medical Research; Biochemistry; Biology; Construction Engineering and Architecture; Engineering; Engineering Sciences; Life Sciences; Medicine
Spatial Coverage University of Stuttgart, Stuttgart, Germany