Identifying a gene knockout strategy using a hybrid of the bat algorithm and flux balance analysis to enhance the production of succinate and lactate in Escherichia coli

2015 ◽  
Vol 20 (2) ◽  
pp. 349-357 ◽  
Author(s):  
Pooi San Chua ◽  
Abdul Hakim Mohamed Salleh ◽  
Mohd Saberi Mohamad ◽  
Safaai Deris ◽  
Sigeru Omatu ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Flux Balance Analysis ◽  
Gene Knockout ◽  
Bat Algorithm ◽  
Flux Balance ◽  
Balance Analysis

Application of dynamic flux balance analysis to an industrial Escherichia coli fermentation

2010 ◽  
Vol 12 (2) ◽  
pp. 150-160 ◽  
Author(s):  
Adam L. Meadows ◽  
Rahi Karnik ◽  
Harry Lam ◽  
Sean Forestell ◽  
Brad Snedecor
Keyword(s):  
Escherichia Coli ◽  
Flux Balance Analysis ◽  
Dynamic Flux Balance Analysis ◽  
Flux Balance ◽  
Balance Analysis

The Metabolic Capabilities of Two Cells in Enterobacteria

2012 ◽  
Vol 424-425 ◽  
pp. 420-423
Author(s):  
Qing Hua Zhou ◽  
Xiao Dian Sun ◽  
Yan Li
Keyword(s):  
Escherichia Coli ◽  
Mathematical Models ◽  
Flux Balance Analysis ◽  
Metabolic Pathway ◽  
Buchnera Aphidicola ◽  
Flux Balance ◽  
Analysis Methods ◽  
Balance Analysis

In this paper, we investigate the metabolic capabilities of two kinds cells belong to enterbacteria. Firstly we develop the mathematical models for Escherichia coli and Buchnera aphidicola Cc based on Flux balance analysis methods. Then we study their capacity of producing the important metabolite Ethanol. Finally, the results show that if the metabolic pathway is more complicated, then more the terminal metabolite-AcCoA is produced.

scholarly journals Gene Knockout Identification Using an Extension of Bees Hill Flux Balance Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Yee Wen Choon ◽  
Mohd Saberi Mohamad ◽  
Safaai Deris ◽  
Chuii Khim Chong ◽  
Sigeru Omatu ◽  
...  
Keyword(s):  
Growth Rate ◽  
Flux Balance Analysis ◽  
Gene Knockout ◽  
Combinatorial Problem ◽  
Production Yield ◽  
Model Organisms ◽  
Computational Time ◽  
Vast Number ◽  
Flux Balance ◽  
Balance Analysis

Microbial strain optimisation for the overproduction of a desired phenotype has been a popular topic in recent years. Gene knockout is a genetic engineering technique that can modify the metabolism of microbial cells to obtain desirable phenotypes. Optimisation algorithms have been developed to identify the effects of gene knockout. However, the complexities of metabolic networks have made the process of identifying the effects of genetic modification on desirable phenotypes challenging. Furthermore, a vast number of reactions in cellular metabolism often lead to a combinatorial problem in obtaining optimal gene knockout. The computational time increases exponentially as the size of the problem increases. This work reports an extension of Bees Hill Flux Balance Analysis (BHFBA) to identify optimal gene knockouts to maximise the production yield of desired phenotypes while sustaining the growth rate. This proposed method functions by integrating OptKnock into BHFBA for validating the results automatically. The results show that the extension of BHFBA is suitable, reliable, and applicable in predicting gene knockout. Through several experiments conducted onEscherichia coli, Bacillus subtilis, andClostridium thermocellumas model organisms, extension of BHFBA has shown better performance in terms of computational time, stability, growth rate, and production yield of desired phenotypes.

scholarly journals Dynamic Flux Balance Analysis to Evaluate the Strain Production Performance on Shikimic Acid Production in Escherichia coli

Metabolites ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 198 ◽  
Author(s):  
Yuki Kuriya ◽  
Michihiro Araki
Keyword(s):  
Escherichia Coli ◽  
Flux Balance Analysis ◽  
Acid Production ◽  
Shikimic Acid ◽  
Strain Improvement ◽  
Glucose Consumption ◽  
Production Performance ◽  
Flux Balance ◽  
Balance Analysis ◽  
Shikimic Acid Production

Flux balance analysis (FBA) is used to improve the microbial production of useful compounds. However, a large gap often exists between the FBA solution and the experimental yield, because of growth and byproducts. FBA has been extended to dynamic FBA (dFBA), which is applicable to time-varying processes, such as batch or fed-batch cultures, and has significantly contributed to metabolic and cultural engineering applications. On the other hand, the performance of the experimental strains has not been fully evaluated. In this study, we applied dFBA to the production of shikimic acid from glucose in Escherichia coli, to evaluate the production performance of the strain as a case study. The experimental data of glucose consumption and cell growth were used as FBA constraints. Bi-level FBA optimization with maximized growth and shikimic acid production were the objective functions. Results suggest that the shikimic acid concentration in the high-shikimic-acid-producing strain constructed in the experiment reached up to 84% of the maximum value by simulation. Thus, this method can be used to evaluate the performance of strains and estimate the milestones of strain improvement.

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