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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.


Related in: MedlinePlus

The effect of cerulenin on fluorescence generated by the sensor circuits. On all three graphs, the solid lines show the cultures challenged with cerulenin, while the segmented lines depict the corresponding untreated cultures. (A) DH5α cells harboring the pBFR1k_RFP_8FapR sensor plasmid in mineral salts medium. (B) DH5α cells harboring the pCFR sensor plasmid in LB medium. Three cultures were tested, originating from three colonies obtained after transformation of the pCFR ligate. (C) DH5α cells harboring the pCFR sensor plasmid from the best performer colony seen in (B), cultured in mineral salts medium.
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Figure 1: The effect of cerulenin on fluorescence generated by the sensor circuits. On all three graphs, the solid lines show the cultures challenged with cerulenin, while the segmented lines depict the corresponding untreated cultures. (A) DH5α cells harboring the pBFR1k_RFP_8FapR sensor plasmid in mineral salts medium. (B) DH5α cells harboring the pCFR sensor plasmid in LB medium. Three cultures were tested, originating from three colonies obtained after transformation of the pCFR ligate. (C) DH5α cells harboring the pCFR sensor plasmid from the best performer colony seen in (B), cultured in mineral salts medium.

Mentions: The core of the malonyl-CoA sensor is an RFP gene driven by the synthetic pFR1 promoter (Liu et al., 2015). pFR1 is a combination of PA1 promoter from phage T7 (Deuschle et al., 1986) and two FapR-binding segments flanking the −10 region. The FapR protein, originating from Bacillus subtilis, dissociates from the DNA upon the binding of malonyl-CoA (Schujman et al., 2003), thereby allowing the E. coli RNA polymerase to transcribe the downstream sequences. The transcription of FapR is driven by a pAra promoter (controlled by the AraC protein), pFR1 is therefore increasingly repressible by elevating the l-arabinose levels. The AraC and FapR transcription factors, as well as RFP are all encoded on pBFR1k_RFP_8FapR, a kanamycin-resistant plasmid constructed by the workgroup of Fuzhong Zhang (Liu et al., 2015). The authors validated the quantitative nature of malonyl-CoA sensing by generating a calibration curve that correlated the fluorescence levels to LC-MS measurements of intracellular malonyl-CoA. In order to use this sensor to compare the malonyl-CoA productivity of our construct collection available on the kanamycin-resistant pRSF vector, we generated a chloramphenicol-resistant version of the plasmid, which we call pCFR (plasmids used in this study are listed in Table S1 in Supplementary Material). The functionality of pCFR, as well as that of the original sensor plasmid was benchmarked with the help of cerulenin. This is an inhibitor of 3-ketoacyl-ACP synthase I and II (D’Agnolo et al., 1973), which participate in the committing step of free fatty acid biosynthesis. The inhibition of these enzymes results in a substantial intracellular accumulation of malonyl-CoA (Davis et al., 2000), and should therefore cause an increase in RFP fluorescence. Indeed, E. coli cells carrying either pBFR1k_RFP_8FapR or pCFR responded to cerulenin with a sharp increase in OD-normalized fluorescence (Figures 1A,B). As a matter of fact, a small scale screening of four pCFR-carrying clones allowed the identification of the most effectively functioning plasmid, which was chosen for all downstream experiments (Figure 1B). As expected, the ratio of RFP/OD values of cerulenin-treated to control cultures was higher in minimal medium than in LB broth (Figure 1C), due to the relatively high background-fluorescence of LB medium (Xu et al., 1999). For this reason, all further measurements were carried out in minimal medium.


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 cerulenin on fluorescence generated by the sensor circuits. On all three graphs, the solid lines show the cultures challenged with cerulenin, while the segmented lines depict the corresponding untreated cultures. (A) DH5α cells harboring the pBFR1k_RFP_8FapR sensor plasmid in mineral salts medium. (B) DH5α cells harboring the pCFR sensor plasmid in LB medium. Three cultures were tested, originating from three colonies obtained after transformation of the pCFR ligate. (C) DH5α cells harboring the pCFR sensor plasmid from the best performer colony seen in (B), cultured in mineral salts medium.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 1: The effect of cerulenin on fluorescence generated by the sensor circuits. On all three graphs, the solid lines show the cultures challenged with cerulenin, while the segmented lines depict the corresponding untreated cultures. (A) DH5α cells harboring the pBFR1k_RFP_8FapR sensor plasmid in mineral salts medium. (B) DH5α cells harboring the pCFR sensor plasmid in LB medium. Three cultures were tested, originating from three colonies obtained after transformation of the pCFR ligate. (C) DH5α cells harboring the pCFR sensor plasmid from the best performer colony seen in (B), cultured in mineral salts medium.
Mentions: The core of the malonyl-CoA sensor is an RFP gene driven by the synthetic pFR1 promoter (Liu et al., 2015). pFR1 is a combination of PA1 promoter from phage T7 (Deuschle et al., 1986) and two FapR-binding segments flanking the −10 region. The FapR protein, originating from Bacillus subtilis, dissociates from the DNA upon the binding of malonyl-CoA (Schujman et al., 2003), thereby allowing the E. coli RNA polymerase to transcribe the downstream sequences. The transcription of FapR is driven by a pAra promoter (controlled by the AraC protein), pFR1 is therefore increasingly repressible by elevating the l-arabinose levels. The AraC and FapR transcription factors, as well as RFP are all encoded on pBFR1k_RFP_8FapR, a kanamycin-resistant plasmid constructed by the workgroup of Fuzhong Zhang (Liu et al., 2015). The authors validated the quantitative nature of malonyl-CoA sensing by generating a calibration curve that correlated the fluorescence levels to LC-MS measurements of intracellular malonyl-CoA. In order to use this sensor to compare the malonyl-CoA productivity of our construct collection available on the kanamycin-resistant pRSF vector, we generated a chloramphenicol-resistant version of the plasmid, which we call pCFR (plasmids used in this study are listed in Table S1 in Supplementary Material). The functionality of pCFR, as well as that of the original sensor plasmid was benchmarked with the help of cerulenin. This is an inhibitor of 3-ketoacyl-ACP synthase I and II (D’Agnolo et al., 1973), which participate in the committing step of free fatty acid biosynthesis. The inhibition of these enzymes results in a substantial intracellular accumulation of malonyl-CoA (Davis et al., 2000), and should therefore cause an increase in RFP fluorescence. Indeed, E. coli cells carrying either pBFR1k_RFP_8FapR or pCFR responded to cerulenin with a sharp increase in OD-normalized fluorescence (Figures 1A,B). As a matter of fact, a small scale screening of four pCFR-carrying clones allowed the identification of the most effectively functioning plasmid, which was chosen for all downstream experiments (Figure 1B). As expected, the ratio of RFP/OD values of cerulenin-treated to control cultures was higher in minimal medium than in LB broth (Figure 1C), due to the relatively high background-fluorescence of LB medium (Xu et al., 1999). For this reason, all further measurements were carried out in minimal medium.

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.


Related in: MedlinePlus