Limits...
ColE1-Plasmid Production in Escherichia coli: Mathematical Simulation and Experimental Validation.

Freudenau I, Lutter P, Baier R, Schleef M, Bednarz H, Lara AR, Niehaus K - Front Bioeng Biotechnol (2015)

Bottom Line: The experimentally determined data for DH5α-pCMV-lacZ reside between 345 ± 203 and 1086 ± 298 RNAI molecules per cell and 22 ± 2 and 75 ± 10 RNAII molecules per cell with an averaged PCN of 1514 ± 1301 and 5806 ± 4828 depending on the measured time point.The hypothesis is that these tRNA molecules would have an enhancing effect on the plasmid production.The in silico analysis predicts that uncharged tRNA molecules would indeed increase the plasmid DNA production.

View Article: PubMed Central - PubMed

Affiliation: Abteilung für Proteom- und Metabolomforschung, Fakultät für Biologie, Universität Bielefeld , Bielefeld , Germany.

ABSTRACT
Plasmids have become very important as pharmaceutical gene vectors in the fields of gene therapy and genetic vaccination in the past years. In this study, we present a dynamic model to simulate the ColE1-like plasmid replication control, once for a DH5α-strain carrying a low copy plasmid (DH5α-pSUP 201-3) and once for a DH5α-strain carrying a high copy plasmid (DH5α-pCMV-lacZ) by using ordinary differential equations and the MATLAB software. The model includes the plasmid replication control by two regulatory RNA molecules (RNAI and RNAII) as well as the replication control by uncharged tRNA molecules. To validate the model, experimental data like RNAI- and RNAII concentration, plasmid copy number (PCN), and growth rate for three different time points in the exponential phase were determined. Depending on the sampled time point, the measured RNAI- and RNAII concentrations for DH5α-pSUP 201-3 reside between 6 ± 0.7 and 34 ± 7 RNAI molecules per cell and 0.44 ± 0.1 and 3 ± 0.9 RNAII molecules per cell. The determined PCNs averaged between 46 ± 26 and 48 ± 30 plasmids per cell. The experimentally determined data for DH5α-pCMV-lacZ reside between 345 ± 203 and 1086 ± 298 RNAI molecules per cell and 22 ± 2 and 75 ± 10 RNAII molecules per cell with an averaged PCN of 1514 ± 1301 and 5806 ± 4828 depending on the measured time point. As the model was shown to be consistent with the experimentally determined data, measured at three different time points within the growth of the same strain, we performed predictive simulations concerning the effect of uncharged tRNA molecules on the ColE1-like plasmid replication control. The hypothesis is that these tRNA molecules would have an enhancing effect on the plasmid production. The in silico analysis predicts that uncharged tRNA molecules would indeed increase the plasmid DNA production.

No MeSH data available.


Related in: MedlinePlus

Growth curve for E. coli DH5α-pSUP 201-3. The growth curve based on OD600 measurements are marked by black circles and the appropriate best-fit curve is indicated in blue. The harvesting time points T1, T2, and T3 are presented as bold big points. The minimum–maximum area, within which the measurement values have to reside, is bordered by the red curve (minimal measured OD600 values) and the green curve (maximal measured OD600 values).
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4555960&req=5

Figure 1: Growth curve for E. coli DH5α-pSUP 201-3. The growth curve based on OD600 measurements are marked by black circles and the appropriate best-fit curve is indicated in blue. The harvesting time points T1, T2, and T3 are presented as bold big points. The minimum–maximum area, within which the measurement values have to reside, is bordered by the red curve (minimal measured OD600 values) and the green curve (maximal measured OD600 values).

Mentions: For growth rate determination at all measured time points, the cells were cultured in minimal medium and the optical density at 600 nm was measured. Growth curves were generated, where the optical density data as the natural logarithm of the measured OD600 values are given on the y-axis, normalized to the initial OD600 value, and the time is given on the x-axis. These growth curves were fitted applying the Matlab function “polyfit.” This function p finds the coefficients of a polynomial p(x) of degree n that fits the optical density data stored in a vector y best in a least-squares sense, where p is a row vector of length n + 1 containing the polynomial coefficients in descending powers, p(1)*x^n + p(2)*x^(n – 1) + … + p(n)*x + p(n + 1). Afterwards a χ2-test was applied to test the quality of the fit. The successfully fitted growth curves are shown in Figures 1 and 2.


ColE1-Plasmid Production in Escherichia coli: Mathematical Simulation and Experimental Validation.

Freudenau I, Lutter P, Baier R, Schleef M, Bednarz H, Lara AR, Niehaus K - Front Bioeng Biotechnol (2015)

Growth curve for E. coli DH5α-pSUP 201-3. The growth curve based on OD600 measurements are marked by black circles and the appropriate best-fit curve is indicated in blue. The harvesting time points T1, T2, and T3 are presented as bold big points. The minimum–maximum area, within which the measurement values have to reside, is bordered by the red curve (minimal measured OD600 values) and the green curve (maximal measured OD600 values).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4555960&req=5

Figure 1: Growth curve for E. coli DH5α-pSUP 201-3. The growth curve based on OD600 measurements are marked by black circles and the appropriate best-fit curve is indicated in blue. The harvesting time points T1, T2, and T3 are presented as bold big points. The minimum–maximum area, within which the measurement values have to reside, is bordered by the red curve (minimal measured OD600 values) and the green curve (maximal measured OD600 values).
Mentions: For growth rate determination at all measured time points, the cells were cultured in minimal medium and the optical density at 600 nm was measured. Growth curves were generated, where the optical density data as the natural logarithm of the measured OD600 values are given on the y-axis, normalized to the initial OD600 value, and the time is given on the x-axis. These growth curves were fitted applying the Matlab function “polyfit.” This function p finds the coefficients of a polynomial p(x) of degree n that fits the optical density data stored in a vector y best in a least-squares sense, where p is a row vector of length n + 1 containing the polynomial coefficients in descending powers, p(1)*x^n + p(2)*x^(n – 1) + … + p(n)*x + p(n + 1). Afterwards a χ2-test was applied to test the quality of the fit. The successfully fitted growth curves are shown in Figures 1 and 2.

Bottom Line: The experimentally determined data for DH5α-pCMV-lacZ reside between 345 ± 203 and 1086 ± 298 RNAI molecules per cell and 22 ± 2 and 75 ± 10 RNAII molecules per cell with an averaged PCN of 1514 ± 1301 and 5806 ± 4828 depending on the measured time point.The hypothesis is that these tRNA molecules would have an enhancing effect on the plasmid production.The in silico analysis predicts that uncharged tRNA molecules would indeed increase the plasmid DNA production.

View Article: PubMed Central - PubMed

Affiliation: Abteilung für Proteom- und Metabolomforschung, Fakultät für Biologie, Universität Bielefeld , Bielefeld , Germany.

ABSTRACT
Plasmids have become very important as pharmaceutical gene vectors in the fields of gene therapy and genetic vaccination in the past years. In this study, we present a dynamic model to simulate the ColE1-like plasmid replication control, once for a DH5α-strain carrying a low copy plasmid (DH5α-pSUP 201-3) and once for a DH5α-strain carrying a high copy plasmid (DH5α-pCMV-lacZ) by using ordinary differential equations and the MATLAB software. The model includes the plasmid replication control by two regulatory RNA molecules (RNAI and RNAII) as well as the replication control by uncharged tRNA molecules. To validate the model, experimental data like RNAI- and RNAII concentration, plasmid copy number (PCN), and growth rate for three different time points in the exponential phase were determined. Depending on the sampled time point, the measured RNAI- and RNAII concentrations for DH5α-pSUP 201-3 reside between 6 ± 0.7 and 34 ± 7 RNAI molecules per cell and 0.44 ± 0.1 and 3 ± 0.9 RNAII molecules per cell. The determined PCNs averaged between 46 ± 26 and 48 ± 30 plasmids per cell. The experimentally determined data for DH5α-pCMV-lacZ reside between 345 ± 203 and 1086 ± 298 RNAI molecules per cell and 22 ± 2 and 75 ± 10 RNAII molecules per cell with an averaged PCN of 1514 ± 1301 and 5806 ± 4828 depending on the measured time point. As the model was shown to be consistent with the experimentally determined data, measured at three different time points within the growth of the same strain, we performed predictive simulations concerning the effect of uncharged tRNA molecules on the ColE1-like plasmid replication control. The hypothesis is that these tRNA molecules would have an enhancing effect on the plasmid production. The in silico analysis predicts that uncharged tRNA molecules would indeed increase the plasmid DNA production.

No MeSH data available.


Related in: MedlinePlus