Presentation Information
[P03-388]A practical design space for constitutive gene expression defined by promoter, RBS, and replication origin combinations in Escherichia coli
○Hidenobu Hirayama1, Akito Odani1, Yoko Hirono-Hara2, Yoshihiro Toya3, Fumio Matsuda3, Kiyotaka Y. Hara4, Jun Ishii1 (1. Graduate School of Science, Technology and Innovation, Kobe University (Japan), 2. 396Bio Inc., 52-1 Yada, Suruga-ku, Shizuoka (Japan), 3. Graduate School of Information Science and Technology, The University of Osaka (Japan), 4. Graduate Division of Nutritional and Environmental Sciences, University of Shizuoka (Japan))
Keywords:
Constitutive expression,Promoter,ribosome binding site,origin of replication,deltarhodopsin,glutathione
[Introduction]
Appropriate design of constitutive expression vectors is essential for purpose-oriented gene expression control. Because promoter–RBS–ori combinations strongly affect output, vector design should consider not only expression level but also target-dependent output, recoverability, and culture-condition dependence. We therefore organized promoter–RBS–ori combinations as coordinates in a common design space to enable rational comparison and selection of expression vector configurations.[Method]
We constructed 45 expression vectors from three constitutive promoters (J23119, J23101, J23116), five RBSs (Strong, B0030, B0034, B0031, B0032), and three ori (pUC, pBR322, p15A). Using EGFP or delta-rhodopsin (dR), we evaluated sequence-confirmed plasmids/transformants under LB, LB + 4 g/L glucose, and M9 + 4 g/L glucose. The same promoter–RBS combinations were also compared in an R6Kγ donor plasmid, a single-copy chromosomal integration strain, and in a p15A-gshF series for glutathione (GSH) production.
[Results]
Under LB, EGFP covered a broad expression range of approximately 102–105. In the same design space, dR also showed stepwise differences in purple pigmentation, but its distribution did not show a complete one-to-one relationship with EGFP. Unevaluable constructs were observed for both EGFP and dR and were more frequent for dR. Across LB, LB + 4 g/L glucose, and M9 + 4 g/L glucose, construct relationships were partly retained for both readouts, although their responses differed. In EGFP, condition dependence mainly appeared as compression of the dynamic range and increased variability. In dR, output changes were accompanied by growth effects, and some constructs showed no growth, reducing the evaluable construct space itself. Relative promoter–RBS relationships were broadly retained within each ori and also in an R6Kγ donor plasmid and single-copy chromosomal integration strain. Based on these results, p15A-LB was used as the reference for subsequent comparison. In the p15A-gshF series, clear construct-dependent differences in GSH production were observed under LB. In chromosomal integration strains, overall GSH production decreased, but some constructs that were not evaluable on the p15A plasmid side became evaluable in the genome context. GSH distributions also changed between LB and M9 + 4 g/L glucose.
[Discussion]
These findings indicate that the 45-vector series should be treated not simply as a series of expression strengths, but as a design space that must be compared in terms of target-dependent output, recoverability, and culture-condition dependence. The same framework remained informative in donor-plasmid and chromosomal contexts and was also reflected in GSH production.
[Conclusion]
This 45-vector design space provides a practical framework for comparing and selecting expression vector configurations while considering expression level, target-dependent output, recoverability, and culture-condition dependence.
Appropriate design of constitutive expression vectors is essential for purpose-oriented gene expression control. Because promoter–RBS–ori combinations strongly affect output, vector design should consider not only expression level but also target-dependent output, recoverability, and culture-condition dependence. We therefore organized promoter–RBS–ori combinations as coordinates in a common design space to enable rational comparison and selection of expression vector configurations.[Method]
We constructed 45 expression vectors from three constitutive promoters (J23119, J23101, J23116), five RBSs (Strong, B0030, B0034, B0031, B0032), and three ori (pUC, pBR322, p15A). Using EGFP or delta-rhodopsin (dR), we evaluated sequence-confirmed plasmids/transformants under LB, LB + 4 g/L glucose, and M9 + 4 g/L glucose. The same promoter–RBS combinations were also compared in an R6Kγ donor plasmid, a single-copy chromosomal integration strain, and in a p15A-gshF series for glutathione (GSH) production.
[Results]
Under LB, EGFP covered a broad expression range of approximately 102–105. In the same design space, dR also showed stepwise differences in purple pigmentation, but its distribution did not show a complete one-to-one relationship with EGFP. Unevaluable constructs were observed for both EGFP and dR and were more frequent for dR. Across LB, LB + 4 g/L glucose, and M9 + 4 g/L glucose, construct relationships were partly retained for both readouts, although their responses differed. In EGFP, condition dependence mainly appeared as compression of the dynamic range and increased variability. In dR, output changes were accompanied by growth effects, and some constructs showed no growth, reducing the evaluable construct space itself. Relative promoter–RBS relationships were broadly retained within each ori and also in an R6Kγ donor plasmid and single-copy chromosomal integration strain. Based on these results, p15A-LB was used as the reference for subsequent comparison. In the p15A-gshF series, clear construct-dependent differences in GSH production were observed under LB. In chromosomal integration strains, overall GSH production decreased, but some constructs that were not evaluable on the p15A plasmid side became evaluable in the genome context. GSH distributions also changed between LB and M9 + 4 g/L glucose.
[Discussion]
These findings indicate that the 45-vector series should be treated not simply as a series of expression strengths, but as a design space that must be compared in terms of target-dependent output, recoverability, and culture-condition dependence. The same framework remained informative in donor-plasmid and chromosomal contexts and was also reflected in GSH production.
[Conclusion]
This 45-vector design space provides a practical framework for comparing and selecting expression vector configurations while considering expression level, target-dependent output, recoverability, and culture-condition dependence.
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