Biomedical subjects

Kwang-Min Lee

Publications and source records attributed to Kwang-Min Lee.

4 recordsLinked to original sources

PubMed2006

Modeling and optimization of biopolymer (polyhydroxyalkanoates) production from ice cream residue by novel statistical experimental design.

Polyhydroxyalkanoates (PHAs) are thermoplastic polyesters synthesized by Ralstonia eutropha and other bacteria as a form of intracellular carbon and energy storage and are accumulated as lipid inclusions in the cytoplasm of these bacteria. The modeling and optimization of PHA production by fermentation from industrial waste (ice cream residue) was studied by employing statistical experimental design methods. A series of iterative experimental designs was used to find optimal factor conditions (medium components and fermentation process time) in the order of fractional factorial design, path of steepest ascent, and full factorial augmented with axial design (rotational central composite design). An optimal range characterized by lipid (15 mg/mL) and % lipid (88%) values was found and further investigated to verify the optimal conditions for PHA production from ice cream (56.68 mL of ice cream or 56.68% ice cream in water [v/v], 5.03 mL of buffer, 1 mL of mineral salts solution, 100 muL of trace element solution, 100 mL of seed culture, and 213.76 h of fermentation time).

Analysis of Variance↗

PubMed2006

Sequential and simultaneous statistical optimization by dynamic design of experiment for peptide overexpression in recombinant Escherichia coli.

The production of recombinant anti-HIV peptide, T-20, in Escherichia coli was optimized by statistical experimental designs (successive designs with multifactors) such as 2(4-1) fractional factorial, 2(3) full factorial, and 2(2) rotational central composite design in order. The effects of media compositions (glucose, NPK sources, MgSO4, and trace elements), induction level, induction timing (optical density at induction process), and induction duration (culture time after induction) on T-20 production were studied by using a statistical response surface method. A series of iterative experimental designs was employed to determine optimal fermentation conditions (media and process factors). Optimal ranges characterized by %T-20 (proportion of peptide to the total cell protein) were observed, narrowed down, and further investigated to determine the optimal combination of culture conditions, which was as follows: 9, 6, 10, and 1 mL of glucose, NPK sources, MgSO4, and trace elements, respectively, in a total of 100 mL of medium inducted at an OD of 0.55-0.75 with 0.7 mM isopropyl-beta-D-thiogalactopyranoside in an induction duration of 4 h. Under these conditions, up to 14% of T-20 was obtained. This statistical optimization allowed the production of T-20 to be increased more than twofold (from 6 to 14%) within a shorter induction duration (from 6 to 4 h) at the shake-flask scale.

Anti-HIV Agents↗

PubMed2006

Statistical medium formulation and process modeling by mixture design of experiment for peptide overexpression in recombinant Escherichia coli.

The medium formulation and robust process modeling for anti-HIV peptide (T-20) production by recombinant Escherichia coli overexpression were studied by employing a crossed experimental design. The crossed design, a mixture design combined with process factor (induction duration), was used to find the optimal medium formulation and process time. The optimal settings for three major components (7.75 mL of NPK sources, 5.5 mL of glucose, and 11.75 mL of MgSO4) characterized by %T-20 (14.45%), the proportion of peptide to the total protein, were observed in a total of 100 mL of medium inducted at an optical density of 0.67 with 0.7 mM isopropyl-beta-D-thiogalactopyranoside) for a 3-h induction duration at shake-flask scale. These conditions were further investigated to find robust process conditions (8.2 mL of NPK sources, 5.6 mL of glucose, and 11.3 mL of MgSO4, and a 3.5-h induction duration time) for T-20 production (13.9%) by applying propagation of error.

Anti-HIV Agents↗

PubMed2006

Statistical experimental design for bioprocess modeling and optimization analysis: repeated-measures method for dynamic biotechnology process.

The statistical design of experiments (DOE) is a collection of predetermined settings of the process variables of interest, which provides an efficient procedure for planning experiments. Experiments on biological processes typically produce long sequences of successive observations on each experimental unit (plant, animal, bioreactor, fermenter, or flask) in response to several treatments (combination of factors). Cell culture and other biotech-related experiments used to be performed by repeated-measures method of experimental design coupled with different levels of several process factors to investigate dynamic biological process. Data collected from this design can be analyzed by several kinds of general linear model (GLM) statistical methods such as multivariate analysis of variance (MANOVA), univariate ANOVA (time split-plot analysis with randomization restriction), and analysis of orthogonal polynomial contrasts of repeated factor (linear coefficient analysis). Last, regression model was introduced to describe responses over time to the different treatments along with model residual analysis. Statistical analysis of biprocess with repeated measurements can help investigate environmental factors and effects affecting physiological and bioprocesses in analyzing and optimizing biotechnology production.

Analysis of Variance↗