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A Sense of Balance: Experimental Investigation and Modeling of a Malonyl-CoA Sensor in Escherichia coli.

Fehér T, Libis V, Carbonell P, Faulon JL - Front Bioeng Biotechnol (2015)

Bottom Line: Moreover, by monitoring the effect of the copy-number of the production plasmid on the dose-response curve of the sensor, we managed to coarse-tune the level of pathway expression to maximize malonyl-CoA synthesis.In addition, we provide an example of the sensor's use in analyzing the effect of inducer or substrate concentrations on production levels.The rational development of models describing sensors, supplemented with the power of high-throughput optimization provide a promising potential for engineering feedback loops regulating enzyme levels to maximize productivity yields of synthetic metabolic pathways.

View Article: PubMed Central - PubMed

Affiliation: Institute of Systems and Synthetic Biology, University of Evry Val d'Essonne , Evry , France ; Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences , Szeged , Hungary.

ABSTRACT
Production of value-added chemicals in microorganisms is regarded as a viable alternative to chemical synthesis. In the past decade, several engineered pathways producing such chemicals, including plant secondary metabolites in microorganisms have been reported; upscaling their production yields, however, was often challenging. Here, we analyze a modular device designed for sensing malonyl-CoA, a common precursor for both fatty acid and flavonoid biosynthesis. The sensor can be used either for high-throughput pathway screening in synthetic biology applications or for introducing a feedback circuit to regulate production of the desired chemical. Here, we used the sensor to compare the performance of several predicted malonyl-CoA-producing pathways, and validated the utility of malonyl-CoA reductase and malonate-CoA transferase for malonyl-CoA biosynthesis. We generated a second-order dynamic linear model describing the relation of the fluorescence generated by the sensor to the biomass of the host cell representing a filter/amplifier with a gain that correlates with the level of induction. We found the time constants describing filter dynamics to be independent of the level of induction but distinctively clustered for each of the production pathways, indicating the robustness of the sensor. Moreover, by monitoring the effect of the copy-number of the production plasmid on the dose-response curve of the sensor, we managed to coarse-tune the level of pathway expression to maximize malonyl-CoA synthesis. In addition, we provide an example of the sensor's use in analyzing the effect of inducer or substrate concentrations on production levels. The rational development of models describing sensors, supplemented with the power of high-throughput optimization provide a promising potential for engineering feedback loops regulating enzyme levels to maximize productivity yields of synthetic metabolic pathways.

No MeSH data available.


Fluorescence response of BL21DE3 cells carrying pCFR sensor plasmid and (A) the empty pRSFduet vector, (B) pRSFmmsA, or (C) pRSFcagg1256. For (B,C), β-alanine was included in the medium. Colors indicate the concentration of IPTG used for induction: dark blue: 0.01 mM; magenta: 0.01 mM; yellow: 1 mM; cyan: 10 mM.
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Figure 3: Fluorescence response of BL21DE3 cells carrying pCFR sensor plasmid and (A) the empty pRSFduet vector, (B) pRSFmmsA, or (C) pRSFcagg1256. For (B,C), β-alanine was included in the medium. Colors indicate the concentration of IPTG used for induction: dark blue: 0.01 mM; magenta: 0.01 mM; yellow: 1 mM; cyan: 10 mM.

Mentions: To compare the malonyl-CoA production efficiencies of alternative malonyl-CoA-producing pathways, at least one representative enzyme for each pathway was cloned, as described earlier (Fehér et al., 2014). Briefly, the matB, atoDA, mmsA, and cagg1256 genes, as well as the accABCD gene complex were expressed from the high-copy plasmid pRSFduet. To provide sufficient amounts of substrate, a MatC was co-expressed with matB and atoDA, and the medium was supplemented with Na-malonate. To elevate the substrate levels for mmsA and cagg1256, cultures were supplemented with β-alanine, which is converted to 3-oxopropanoate (malonate semialdehyde) by the cell’s endogenous 4-aminobutyrate aminotransferase. In every case, the fluorescence/OD values were monitored over time after growing the cells in various IPTG concentrations. Cells carrying the empty pRSFduet plasmid (besides the sensor plasmid) were used as a negative control. Based on their response, the strains carrying the various constructs fell into either one of the two following categories: (i) the cells exhibited growth and a dose-dependent fluorescence/OD response to IPTG (pRSFmmsA and pRSFcagg) (Figure 3) or (ii) the cells exhibited absolutely no growth upon IPTG induction in minimal medium (pRSFMaccABCD and pRSFatoDA) (Figures 4A,B). It is important to note that certain cells of the latter category also gave a seemingly dose-dependent response to IPTG (such as pRSFatoDA), but their fluorescence and OD values were practically unchanged during the course of the experiment, most probably indicating that the trend in their ratio is an artifact (Figure S1 in Supplementary Material). Interestingly, both types of responses were seen with pRSFmatCmatB-carrying cells, in a quite irreproducible manner (see Discussion and Figures 4C,D and Figure S2 in Supplementary Material). The growth curves obtained by inducing strains carrying various producer plasmids are summarized on Figure S3 in Supplementary Material.


A Sense of Balance: Experimental Investigation and Modeling of a Malonyl-CoA Sensor in Escherichia coli.

Fehér T, Libis V, Carbonell P, Faulon JL - Front Bioeng Biotechnol (2015)

Fluorescence response of BL21DE3 cells carrying pCFR sensor plasmid and (A) the empty pRSFduet vector, (B) pRSFmmsA, or (C) pRSFcagg1256. For (B,C), β-alanine was included in the medium. Colors indicate the concentration of IPTG used for induction: dark blue: 0.01 mM; magenta: 0.01 mM; yellow: 1 mM; cyan: 10 mM.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4389729&req=5

Figure 3: Fluorescence response of BL21DE3 cells carrying pCFR sensor plasmid and (A) the empty pRSFduet vector, (B) pRSFmmsA, or (C) pRSFcagg1256. For (B,C), β-alanine was included in the medium. Colors indicate the concentration of IPTG used for induction: dark blue: 0.01 mM; magenta: 0.01 mM; yellow: 1 mM; cyan: 10 mM.
Mentions: To compare the malonyl-CoA production efficiencies of alternative malonyl-CoA-producing pathways, at least one representative enzyme for each pathway was cloned, as described earlier (Fehér et al., 2014). Briefly, the matB, atoDA, mmsA, and cagg1256 genes, as well as the accABCD gene complex were expressed from the high-copy plasmid pRSFduet. To provide sufficient amounts of substrate, a MatC was co-expressed with matB and atoDA, and the medium was supplemented with Na-malonate. To elevate the substrate levels for mmsA and cagg1256, cultures were supplemented with β-alanine, which is converted to 3-oxopropanoate (malonate semialdehyde) by the cell’s endogenous 4-aminobutyrate aminotransferase. In every case, the fluorescence/OD values were monitored over time after growing the cells in various IPTG concentrations. Cells carrying the empty pRSFduet plasmid (besides the sensor plasmid) were used as a negative control. Based on their response, the strains carrying the various constructs fell into either one of the two following categories: (i) the cells exhibited growth and a dose-dependent fluorescence/OD response to IPTG (pRSFmmsA and pRSFcagg) (Figure 3) or (ii) the cells exhibited absolutely no growth upon IPTG induction in minimal medium (pRSFMaccABCD and pRSFatoDA) (Figures 4A,B). It is important to note that certain cells of the latter category also gave a seemingly dose-dependent response to IPTG (such as pRSFatoDA), but their fluorescence and OD values were practically unchanged during the course of the experiment, most probably indicating that the trend in their ratio is an artifact (Figure S1 in Supplementary Material). Interestingly, both types of responses were seen with pRSFmatCmatB-carrying cells, in a quite irreproducible manner (see Discussion and Figures 4C,D and Figure S2 in Supplementary Material). The growth curves obtained by inducing strains carrying various producer plasmids are summarized on Figure S3 in Supplementary Material.

Bottom Line: Moreover, by monitoring the effect of the copy-number of the production plasmid on the dose-response curve of the sensor, we managed to coarse-tune the level of pathway expression to maximize malonyl-CoA synthesis.In addition, we provide an example of the sensor's use in analyzing the effect of inducer or substrate concentrations on production levels.The rational development of models describing sensors, supplemented with the power of high-throughput optimization provide a promising potential for engineering feedback loops regulating enzyme levels to maximize productivity yields of synthetic metabolic pathways.

View Article: PubMed Central - PubMed

Affiliation: Institute of Systems and Synthetic Biology, University of Evry Val d'Essonne , Evry , France ; Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences , Szeged , Hungary.

ABSTRACT
Production of value-added chemicals in microorganisms is regarded as a viable alternative to chemical synthesis. In the past decade, several engineered pathways producing such chemicals, including plant secondary metabolites in microorganisms have been reported; upscaling their production yields, however, was often challenging. Here, we analyze a modular device designed for sensing malonyl-CoA, a common precursor for both fatty acid and flavonoid biosynthesis. The sensor can be used either for high-throughput pathway screening in synthetic biology applications or for introducing a feedback circuit to regulate production of the desired chemical. Here, we used the sensor to compare the performance of several predicted malonyl-CoA-producing pathways, and validated the utility of malonyl-CoA reductase and malonate-CoA transferase for malonyl-CoA biosynthesis. We generated a second-order dynamic linear model describing the relation of the fluorescence generated by the sensor to the biomass of the host cell representing a filter/amplifier with a gain that correlates with the level of induction. We found the time constants describing filter dynamics to be independent of the level of induction but distinctively clustered for each of the production pathways, indicating the robustness of the sensor. Moreover, by monitoring the effect of the copy-number of the production plasmid on the dose-response curve of the sensor, we managed to coarse-tune the level of pathway expression to maximize malonyl-CoA synthesis. In addition, we provide an example of the sensor's use in analyzing the effect of inducer or substrate concentrations on production levels. The rational development of models describing sensors, supplemented with the power of high-throughput optimization provide a promising potential for engineering feedback loops regulating enzyme levels to maximize productivity yields of synthetic metabolic pathways.

No MeSH data available.