Cell density-dependent auto-inducible promoters for expression of recombinant proteins in Pseudomonas putida.
Annika MeyersChristoph FurtmannKatrin GesingIasson E P TozakidisJoachim JosePublished in: Microbial biotechnology (2019)
Inducible promoters such as Plac are of limited usability for industrial protein production with Pseudomonas putida. We therefore utilized cell density-dependent auto-inducible promoters for recombinant gene expression in P. putida KT2440 based on the RoxS/RoxR Quorum Sensing (QS) system of the bacterium. To this end, genetic regions upstream of the RoxS/RoxR-regulated genes ddcA (PR ox132 ) and PP_3332 (PR ox306 ) were inserted into plasmids that mediated the expression of superfolder green fluorescent protein (sfGFP) and surface displayed mCherry, confirming their promoter functionalities. Mutation of the Pribnow box of PR ox306 to the σ70 consensus sequence (PR ox3061 ) resulted in a more than threefold increase of sfGFP production. All three promoters caused cell density-dependent expression, starting transcription at optical densities (OD578 ) of approximately 1.0 (PR ox132 , PR ox306 ) or 0.7 (PR ox3061 ) as determined by RT-qPCR. The QS dependency of PR ox306 was further shown by cultivating P. putida in media that had already been used for cultivation and thus contained bacterial signal molecules. The longer P. putida had grown in these media before, the earlier protein expression in freshly inoculated P. putida appeared with PR ox306 . This confirmed previous findings that a bacterial compound accumulates within the culture and induces protein expression.
Keyphrases
- gene expression
- poor prognosis
- low density lipoprotein
- binding protein
- single cell
- transcription factor
- cell therapy
- healthcare
- dna methylation
- stem cells
- staphylococcus aureus
- long non coding rna
- amino acid
- high resolution
- mass spectrometry
- pseudomonas aeruginosa
- bone marrow
- cystic fibrosis
- wastewater treatment
- cell free
- multidrug resistant
- candida albicans
- genome wide identification
- genome wide analysis