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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.


The effect of administering the substrate on the level of fluorescence obtained upon induction of malonyl-CoA production. Hashed bars represent the effect of IPTG on the fluorescence obtained at OD = 0.6 with constructs (A) pACYCmatCmatB, (B) pACYCmatCatoDA, and (C) pRSFmmsA. Gray bars depict the peak fluorescence detected when inducing the same constructs in the presence of their substrate: Na-malonate for matCmatB and matCatoDA and β-alanine for mmsA. The sensor plasmid was pBFR1k_RFP_8FapR for (A,B) and pCFR for (C). Asterisks indicate a significantly different fluorescence caused by the substrate (p < 0.05).
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Figure 8: The effect of administering the substrate on the level of fluorescence obtained upon induction of malonyl-CoA production. Hashed bars represent the effect of IPTG on the fluorescence obtained at OD = 0.6 with constructs (A) pACYCmatCmatB, (B) pACYCmatCatoDA, and (C) pRSFmmsA. Gray bars depict the peak fluorescence detected when inducing the same constructs in the presence of their substrate: Na-malonate for matCmatB and matCatoDA and β-alanine for mmsA. The sensor plasmid was pBFR1k_RFP_8FapR for (A,B) and pCFR for (C). Asterisks indicate a significantly different fluorescence caused by the substrate (p < 0.05).

Mentions: To test whether providing the substrates of malonyl-CoA synthesis in the growth medium offers a measurable advantage in the product levels, we repeated the experiment for, pACYCmatCmatB and pACYCmatCatoDA with and without Na-malonate as well as for pRSFmmsA and pRSFcagg with and without β-alanine. For pACYCmatCmatB, we observed significantly boosted production at 0.3 and 0.6 mM IPTG (Figure 8A). However, the presence of Na-malonate significantly hindered the performance of pACYCmatCatoDA at IPTG concentrations of 0.3 mM and above (Figure 8B). Similarly, supplementing β-alanine to pRSFmmsA seemed to have a negative effect at 0.6 mM IPTG induction (Figure 8C). No significant effect was seen for adding the substrate to pRSFcagg (not shown).


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)

The effect of administering the substrate on the level of fluorescence obtained upon induction of malonyl-CoA production. Hashed bars represent the effect of IPTG on the fluorescence obtained at OD = 0.6 with constructs (A) pACYCmatCmatB, (B) pACYCmatCatoDA, and (C) pRSFmmsA. Gray bars depict the peak fluorescence detected when inducing the same constructs in the presence of their substrate: Na-malonate for matCmatB and matCatoDA and β-alanine for mmsA. The sensor plasmid was pBFR1k_RFP_8FapR for (A,B) and pCFR for (C). Asterisks indicate a significantly different fluorescence caused by the substrate (p < 0.05).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 8: The effect of administering the substrate on the level of fluorescence obtained upon induction of malonyl-CoA production. Hashed bars represent the effect of IPTG on the fluorescence obtained at OD = 0.6 with constructs (A) pACYCmatCmatB, (B) pACYCmatCatoDA, and (C) pRSFmmsA. Gray bars depict the peak fluorescence detected when inducing the same constructs in the presence of their substrate: Na-malonate for matCmatB and matCatoDA and β-alanine for mmsA. The sensor plasmid was pBFR1k_RFP_8FapR for (A,B) and pCFR for (C). Asterisks indicate a significantly different fluorescence caused by the substrate (p < 0.05).
Mentions: To test whether providing the substrates of malonyl-CoA synthesis in the growth medium offers a measurable advantage in the product levels, we repeated the experiment for, pACYCmatCmatB and pACYCmatCatoDA with and without Na-malonate as well as for pRSFmmsA and pRSFcagg with and without β-alanine. For pACYCmatCmatB, we observed significantly boosted production at 0.3 and 0.6 mM IPTG (Figure 8A). However, the presence of Na-malonate significantly hindered the performance of pACYCmatCatoDA at IPTG concentrations of 0.3 mM and above (Figure 8B). Similarly, supplementing β-alanine to pRSFmmsA seemed to have a negative effect at 0.6 mM IPTG induction (Figure 8C). No significant effect was seen for adding the substrate to pRSFcagg (not shown).

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.