Stable Platform for Mevalonate Bioproduction from CO 2 .
Marco GaravagliaCallum McGregorRajesh Reddy BommareddyVictor IrorereChristian ArenasAlberto RobazzaNigel Peter MintonKatalin KovacsPublished in: ACS sustainable chemistry & engineering (2024)
Stable production of value-added products using a microbial chassis is pivotal for determining the industrial suitability of the engineered biocatalyst. Microbial cells often lose the multicopy expression plasmids during long-term cultivations. Owing to the advantages related to titers, yields, and productivities when using a multicopy expression system compared with genomic integrations, plasmid stability is essential for industrially relevant biobased processes. Cupriavidus necator H16, a facultative chemolithoautotrophic bacterium, has been successfully engineered to convert inorganic carbon obtained from CO 2 fixation into value-added products. The application of this unique capability in the biotech industry has been hindered by C . necator H16 inability to stably maintain multicopy plasmids. In this study, we designed and tested plasmid addiction systems based on the complementation of essential genes. Among these, implementation of a plasmid addiction tool based on the complementation of mutants lacking RubisCO, which is essential for CO 2 fixation, successfully stabilized a multicopy plasmid. Expressing the mevalonate pathway operon (MvaES) using this addiction system resulted in the production of ∼10 g/L mevalonate with carbon yields of ∼25%. The mevalonate titers and yields obtained here using CO 2 are the highest achieved to date for the production of C6 compounds from C1 feedstocks.
Keyphrases
- escherichia coli
- poor prognosis
- crispr cas
- microbial community
- minimally invasive
- klebsiella pneumoniae
- induced apoptosis
- healthcare
- primary care
- genome wide
- cell cycle arrest
- binding protein
- high throughput
- heavy metals
- cell death
- dna methylation
- risk assessment
- endoplasmic reticulum stress
- transcription factor
- wild type
- drug induced
- bioinformatics analysis