Statistical optimization for the production of recombinant cold-adapted superoxide dismutase in<i>E. coli</i>using response surface methodology

Wang, Yatong; Wang, Quanfu; Wang, Yifan; Han, Han; Hou, Yanhua; Shi, Yonglei

doi:10.1080/21655979.2017.1303589

Cited by 11 publications

(7 citation statements)

References 38 publications

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“…These parameters generate statistical data, which were further used for analysis of BBD/quadric models showing the significant value for the optimization of biodegradation. The resultant data were used to plot the response surfaces curves (Wang et al 2017).…”

Section: Experimental Design Degradation Optimization Studies and Stmentioning

confidence: 99%

“…The anaerobic reactor reaction rate was increased in initial stage due to presence of volatile fatty acids in waste water. Higher loading rate caused many problems, like acidification and lower the efficiency of degradation (COD removal) (Liang et al 2016;Wang et al 2017). The anaerobic reactor degradation occurs in three stages: (1) adjustment phase, (2) initiation of degradation, and (3) steady-state degradation.…”

Section: Biodegradation Study In Pilot Reactormentioning

confidence: 99%

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Characterization, optimization and kinetics study of acetaminophen degradation by Bacillus drentensis strain S1 and waste water degradation analysis

Chopra

Kumar

2020

Bioresour. Bioprocess.

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Background: In this study, the biodegradation of N-acetyl-para-aminophenol also known as acetaminophen (APAP, paracetamol) was studied by bacterial strain Bacillus drentensis strain S1 (accession no. KY623719) isolated from sewage sample. Results: The Bacillus drentensis strain S1 was isolated from the sewage sample using the enrichment culture method. As per our knowledge this is the first Bacillus drentensis strain reported for the degradation of APAP. In this study a 20-L batch reactor was employed for degradation of APAP. The maximum specific growth rate (μ max) was observed at 400 mg/L concentration of APAP. The pilot-scale anaerobic batch reactor of was stable and self-buffered. The degradation in pilot-scale reactor was slow as compared to batch experiments due to fluctuation in pH and exhaustion of nutrients. Design-Expert ® software was used for optimization of conditions for APAP degradation; such as temperature (40 °C), pH (7.0), concentration of APAP (300 g/L) and agitation speed (165 rpm). The FTIR and GC-MS were used to identify the degradation metabolites. The intermediates of degradation like 2-isopropyl-5-methylcyclohexanone and phenothiazine were observed, based on these results the metabolic pathway has been predicted. Conclusions: The optimization, kinetic, batch study and pilot study indicates the potential of Bacillus drentensis strain S1 for degradation of acetaminophen. The experimental design, optimization and statistical analysis were performed by Design Expert ® software. The optimal growth condition for Bacillus drentensis strain S1 was found to be at temperature 40 °C, pH 7, acetaminophen at concentration of 300 (mg/L) and agitation speed 165 rpm. The GC-MS and FTIR was used for identification of metabolites produced during acetaminophen degradation and the partial metabolic pathway for degradation of acetaminophen was also proposed .

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Section: Experimental Design Degradation Optimization Studies and Stmentioning

confidence: 99%

Section: Biodegradation Study In Pilot Reactormentioning

confidence: 99%

Characterization, optimization and kinetics study of acetaminophen degradation by Bacillus drentensis strain S1 and waste water degradation analysis

Chopra

Kumar

2020

Bioresour. Bioprocess.

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“…Fermentation activity could be determined by CO 2 production [25], cell concentration [26], superoxide dismutase/acid phosphatase activity [27,28], proline/malonaldehyde concentration [29,30], relative electrolytic leakage [31], etc. Here, we used the CO 2 production method described in previous papers with a few modifications [32][33][34][35].…”

Section: Ethanol Tolerance Assay and Determination Of Fermentation Prmentioning

confidence: 99%

Improvement of Ethanol Tolerance by Inactive Protoplast Fusion in Saccharomyces cerevisiae

Yang²,

Yin³

et al. 2020

BioMed Research International

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Saccharomyces cerevisiae is a typical fermentation yeast in beer production. Improving ethanol tolerance of S. cerevisiae will increase fermentation efficiency, thereby reducing capital costs. Here, we found that S. cerevisiae strain L exhibited a higher ethanol tolerance (14%, v/v) than the fermentative strain Q (10%, v/v). In order to enhance the strain Q ethanol tolerance but preserve its fermentation property, protoplast fusion was performed with haploids from strain Q and L. The fusant Q/L-f2 with 14% ethanol tolerance was obtained. Meanwhile, the fermentation properties (flocculability, SO2 production, α-N assimilation rate, GSH production, etc.) of Q/L-f2 were similar to those of strain Q. Therefore, our works established a series of high ethanol-tolerant strains in beer production. Moreover, this demonstration of inactivated protoplast fusion in industrial S. cerevisiae strain opens many doors for yeast-based biotechnological applications.

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“…The Adjusted R 2 is used to check the adequacy of the model by measuring the amount of variation about the mean derived from the model; the closer the value is to 1, the better it describes the model [130]. For example, in Table 9, the R 2 = 0.9971 indicates the significance of regression of the fitting equation and therefore, adequacy of discrimination, indicating that only 0.29% of the total variation could not be explained by the fitting equation [142]. When R 2 = 99.71%, Adj- R 2 = 99.63%, Pred- R 2 = 99.48% are in good agreement with each other (as in Table 9), this provides confidence in the accuracy of the model [156].…”

Section: A Suggested Doe Workflow For Recombinant Protein Productionmentioning

confidence: 99%

The Goldilocks Approach: A Review of Employing Design of Experiments in Prokaryotic Recombinant Protein Production

Uhoraningoga¹,

Kinsella²,

Henehan³

et al. 2018

Bioengineering

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The production of high yields of soluble recombinant protein is one of the main objectives of protein biotechnology. Several factors, such as expression system, vector, host, media composition and induction conditions can influence recombinant protein yield. Identifying the most important factors for optimum protein expression may involve significant investment of time and considerable cost. To address this problem, statistical models such as Design of Experiments (DoE) have been used to optimise recombinant protein production. This review examines the application of DoE in the production of recombinant proteins in prokaryotic expression systems with specific emphasis on media composition and culture conditions. The review examines the most commonly used DoE screening and optimisation designs. It provides examples of DoE applied to optimisation of media and culture conditions.

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Statistical optimization for the production of recombinant cold-adapted superoxide dismutase inE. coliusing response surface methodology

Cited by 11 publications

References 38 publications

Characterization, optimization and kinetics study of acetaminophen degradation by Bacillus drentensis strain S1 and waste water degradation analysis

Characterization, optimization and kinetics study of acetaminophen degradation by Bacillus drentensis strain S1 and waste water degradation analysis

Improvement of Ethanol Tolerance by Inactive Protoplast Fusion in Saccharomyces cerevisiae

The Goldilocks Approach: A Review of Employing Design of Experiments in Prokaryotic Recombinant Protein Production

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