Optimization of an induction strategy for improving interferon‐α2b production in the periplasm of <i>Escherichia coli</i> using response surface methodology

Azaman, Siti Nor Ani; Ramanan, Ramakrishnan Nagasundara; Tan, Joo Shun; Rahim, Raha Abdul; Abdullah, Md. Pauzi; Ariff, Arbakariya B.

doi:10.1042/ba20100104

Cited by 23 publications

(13 citation statements)

References 41 publications

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“…A second order polynomial equation was found to be useful for the development of efficient bioprocess for cellulase production. Second-order polynomial models were used to correlate the abovementioned factors to soluble periplasmic IFN-α2b formation and percentage of soluble IFN-α2b translocated to the periplasmic space of E. coli and the models were found to be significant and subsequently validated [23]. Statistical optimization of fermentation conditions were reported to enhanced the cellulase production to 2995.20 ± 200.00 IU/mL, which was 9.91-fold higher than the activity under unoptimized basal medium (302.2 IU/mL) [24].…”

Section: Resultsmentioning

confidence: 99%

Application of Statistically Based Experimental Designs to Optimize Cellulase Production and Identification of Gene

Thakkar

Saraf

2014

Nat. Prod. Bioprospect.

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A natural bacterial strain identified as Bacillus amyloliquefaciens MBAA3 using 16S rDNA partial genome sequencing has been studied for optimization of cellulase production. Statistical screening of media components for production of cellulase by B. amyloliquefaciens MBAA3 was carried out by Plackett–Burman design. Plackett–Burman design showed CMC, MgSO4 and pH as significant components influencing the cellulase production from the media components screened by Plackett-Burman fractional factorial design. The optimum concentrations of these significant parameters were determined employing the response surface central composite design, involving three factors and five levels was adopted to acquire the best medium for the production of cellulase enzyme revealed concentration of CMC (1.84 g), MgSO4 (0.275 g), and pH (8.5) in media for highest enzyme production. Response surface counter plots revealed that middle level of MgSO4 and middle level of CMC, higher level of CMC and lower level of pH and higher level of MgSO4 with lower level of pH increase the production of cellulase. After optimization cellulase activity increased by 6.81 fold. Presence of cellulase gene in MBAA3 was conformed by the amplification of genomic DNA of MBAA3. A PCR product of cellulase gene of 1500 bp was successfully amplified. The amplified gene was conformed by sequencing the amplified product and sequence was deposited in the gene bank under the accession number KF929416.Graphical AbstractResponse surface graph showing interaction effects between concentration of a CMC and MgSO4. b pH and CMC. c MgSO4 and pH

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Section: Resultsmentioning

confidence: 99%

Application of Statistically Based Experimental Designs to Optimize Cellulase Production and Identification of Gene

Thakkar

Saraf

2014

Nat. Prod. Bioprospect.

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“…The classical technique of one parameter at a time is time consuming and not effective for the identification of interactions and also for the predictions of parameters involved in the process. Nowadays, mathematical methods such as response surface methodology (RSM) [1,11,20,23] and artificial neural network (ANN) [9,13,27] are commonly used for modelling and optimization of processes.…”

Section: Introductionmentioning

confidence: 99%

Comparison of the estimation capabilities of response surface methodology and artificial neural network for the optimization of recombinant lipase production by E. coli BL21

Nelofer

Ramanan

Rahman

et al. 2012

Journal of Industrial Microbiology and Biotechnology

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Response surface methodology (RSM) and artificial neural network (ANN) were used to optimize the effect of four independent variables, viz. glucose, sodium chloride (NaCl), temperature and induction time, on lipase production by a recombinant Escherichia coli BL21. The optimization and prediction capabilities of RSM and ANN were then compared. RSM predicted the dependent variable with a good coefficient of correlation determination (R² and adjusted R² values for the model. Although the R (2) value showed a good fit, absolute average deviation (AAD) and root mean square error (RMSE) values did not support the accuracy of the model and this was due to the inferiority in predicting the values towards the edges of the design points. On the other hand, ANN-predicted values were closer to the observed values with better R², adjusted R², AAD and RMSE values and this was due to the capability of predicting the values throughout the selected range of the design points. Similar to RSM, ANN could also be used to rank the effect of variables. However, ANN could not predict the interactive effect between the variables as performed by RSM. The optimum levels for glucose, NaCl, temperature and induction time predicted by RSM are 32 g/L, 5 g/L, 32°C and 2.12 h, and those by ANN are 25 g/L, 3 g/L, 30°C and 2 h, respectively. The ANN-predicted optimal levels gave higher lipase activity (55.8 IU/mL) as compared to RSM-predicted levels (50.2 IU/mL) and the predicted lipase activity was also closer to the observed data at these levels, suggesting that ANN is a better optimization method than RSM for lipase production by the recombinant strain.

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“…The levels of the significant factors and the interaction effects between these factors were analyzed and optimized using Central Composite design as described previously (Azaman et al 2010;Bezerra et al 2008;Wu et al 2010;Farliahati et al 2010). In this study, 30 trials were included and the independent variables were studied at three different levels.…”

Section: Optimization For Conditions Of Act Productionmentioning

confidence: 99%

Isolation, identification and fermentation conditions of highly acetoin-producing acetic acid bacterium from Liangzhou fumigated vinegar in China

Zhao

Yun

2015

Ann Microbiol

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Liangzhou fumigated vinegar is famous in China for its distinct flavor. How to enhance flavor in traditional fermented foods, such as vinegar, has attracted a large interest in recent years. Acetoin (ACT) is a precursor of tetramethylpyrazine (TTMP), a popular food flavor found in different traditional fermented foods. We obtained 200 acid-producing isolates from the solid fermentative substrate of Liangzhou fumigated vinegar by the method of forming transparent zones on GYC agar, and 28 bacteria producing ACT by Voges-Proskauer colorimetric assay and gas chromatography analysis, including 15 strains of Acetobacter, eight strains of Lactobacillus and five strains of Staphylococcus. Based on ACT level, the isolate C92 with the highest yield was selected for further analysis. It was identified as Acetobacter pasteurianus by physiological and biochemical characteristics, as well as 16S rRNA gene sequence similarities. We examined the ACT level of strain C92 under different conditions, and found that a temperature of 31.31°C, pH of 6.67, shaking speed of 209 rpm, and inoculation volume of 8.27 % were the best conditions for strain C92 to produce a yield of 19.04 g/L at 40 h postculture. In a time-ACT curve, ACT reached the maximum value at 40 h and then decreased afterward, suggesting that ACT produced by C92 is a growth-associated primary metabolite from sugar. Therefore, the C92 isolate is regarded as a strain with promising ACT-production ability in vinegar. More studies are needed before C92 is applied in the industrial production of vinegar.

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Optimization of an induction strategy for improving interferon‐α2b production in the periplasm of Escherichia coli using response surface methodology

Cited by 23 publications

References 41 publications

Application of Statistically Based Experimental Designs to Optimize Cellulase Production and Identification of Gene

Application of Statistically Based Experimental Designs to Optimize Cellulase Production and Identification of Gene

Comparison of the estimation capabilities of response surface methodology and artificial neural network for the optimization of recombinant lipase production by E. coli BL21

Isolation, identification and fermentation conditions of highly acetoin-producing acetic acid bacterium from Liangzhou fumigated vinegar in China

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