Enhanced production of human Cytochrome P450 2C9 by Escherichia coli BL21(DE3)pLysS through the novel use of grey relational analysis and Plackett–Burman design

Abstract

Cytochrome P450 (CYP, P450) 2C9 is one of three human microsomal CYPs in subfamily 2C that contribute extensively to the hepatic metabolism of therapeutic drugs. The enhancement of recombinant CYP2C9 expression of a transformed E. coli strain is essential for the development of an efficient large-scale bioprocess. The recombinant CYP2C9 production is influenced by various factors, especially the medium components. The aim of this study is to optimize the culture medium of the recombinant E. coli, to determine the influence order of 11 factors, and to improve the yield of heterologously expressed CYP2C9. Plackett–Burman (PB) design, a statistical methodology, was used to screen 11 nutrients and medium components for the production of human CYP2C9 from E. coli BL21(DE3)pLysS harboring plasmid pCW2C9dH in aerobic shaking flask cultures. The experimental data were subject to statistical analysis for calculating the regression coefficients. The matrix of PB design was also used to construct the series that is needed for grey relational analysis (GRA), an approach totally different from traditional statistical analysis used to calculate the relational grade between two sequence data, to determine the influence priority of 11 parameters. Influence priority: glycerol > δ-ALA > IPTG = ampicillin > chloramphenicol = inoculum density > peptone > thiamine > trace elements > NH₄Cl > MgSO₄. The coefficient for the individual factor estimated from PB design agrees the conclusion of GRA. This is the first report that combined two powerful analysis methods for the enhanced production of recombinant protein.

Appendix

Those systems that lack information such as structure messages, operation mechanisms, and behavior documents can be referred to as grey systems. GRA can be used to represent the grade of correlation between two sequences so that the distance of two factors can be measured discretely.

A so-called grey relational space contains several series: one is used as the fix reference series x ₀, and the others are series x _i to be compared as shown below

$$ x_{0} = {\text{ }}(x_{0} (1),{\text{ }}x_{0} (2), \ldots ,{\text{ }}x_{0} (n)), $$

$$ x_{i} = (x_{i} (1),{\text{ }}x_{i} (2), \ldots ,{\text{ }}x_{i} (n)),{\text{ }}i = 1,{\text{ }}2, \ldots ,{\text{ }}m. $$

All numbers in the series should be pretreated to locate the value of each datum in [0, 1]. The pretreatment can be performed using the following approach,

$$ x^{*}_{i} {\text{(}}k{\text{) = }}\frac{{\max [x^{{(0)}}_{i} {\text{(}}k{\text{)] }} - {\text{ }}x^{{(0)}}_{i} {\text{(}}k{\text{)}}}} {{\max [x^{{(0)}}_{i} {\text{(}}k{\text{)] }} - {\text{ min[}}x^{{(0)}}_{i} {\text{(}}k{\text{)]}}}}, $$

where x ^* _i (k) is the normalized value of each elements in each series.

An m × n matrix X can consist of m series

$$ X = {\left[ \eqalign{{} x_{1} (1)x_{1} (2) \cdots x_{1} (n) \cr x_{2} (1)x_{2} (2) \cdots x_{2} (n) \cr \ldots \cr \ldots \cr x_{m} (1)x_{m} (2) \cdots x_{m} (n) \cr }<!endaligned> \right]}. $$

The elements in each row of the above matrix are subtracted by the elements of the reference series, thus another matrix Δ is obtained:

$$ \Delta = {\left[ \eqalign{{} \Delta _{ {01}} (1)\Delta _{ {01}} (2) \cdots \Delta _{ {01}} (n) \cr \Delta _{ {02}} (1)\Delta _{ {02}} (2) \cdots \Delta _{ {02}} (n) \cr \ldots \cr \ldots \cr \Delta _{ {0m}} (1)\Delta _{ {0m}} (2) \cdots \Delta _{ {0m}} (n) \cr }<!endaligned> \right]}, $$

where Δ_0j (k) = |x _j (k)−x ₀(k)|. Δ_max is the elements of maximum value in the matrix, while Δ_min is the elements of minimum value in the matrix. The grey relational coefficient γ _0j (k) can then be expressed as

$$ \gamma _{ {0j}} {{(k) = }}\frac{{\Delta _{ {\min }} + \zeta \cdot \Delta _{ {\max }} }} {{\Delta _{ {0j}} {\text{(k)}} + \zeta \cdot \Delta _{ {\max }} }}, $$

(1)

where the value of the coefficient ζ is in [0, 1].

The grey relational grade is defined as the average of all grey relational coefficients, i.e.,

$$ \gamma (x_{0},x_{j}) = \frac{1} {n}{\sum\limits_{k = 1}^n {\gamma_{0j}(k)} }. $$

(2)

therefore, the influence sequence of the affecting factors of the system can be analyzed with the value of the grey relational grade.