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Open Access Biostatistics & Bioinformatic

Escherichia coli Genome-Scale Metabolic Models Could Guide Construction of Proof-of-Principle Strains

Bashir Sajo Mienda*

Department of Microbiology & Biotechnology, Federal University Dutse, Nigeria

*Corresponding author: Bashir Sajo Mienda, Department of Microbiology & Biotechnology, Faculty of Science, Federal University Dutse, PMB 7156 Ibrahim Aliyu Bypass, Dutse, Jigawa, Nigeria

Submission: April 16, 2018;Published: April 26, 2018

DOI: 10.31031/OABB.2018.01.000518

ISSN: 2578-0247
Volume1 Issue4

Opinion

Escherichia coli genome-scale metabolic models (GEMs) have been published with ability to predict metabolic engineering capabilities that could be consistent with experimental measurements. However, the GEMs have limited scope, and the models are of two types, metabolism models (M-model), and metabolism and gene expression (ME-model) that could guide the constructions of proof-of-principle strains of particularly E. coli bacterium that may find applications in metabolic engineering strategies, synthetic biology [1], and beyond. GEMs have been clearly established to be capable of predicting metabolic engineering capabilities and could sometime lead to biological discoveries for missing reactions and/or missing gene functions [2-4]. In addition, systems metabolic engineering has proof useful with the use of GEMs where time consuming experimental trial and error was shortened by predicting engineering strategies using GEMs. Although sometimes prediction could fail to agree with experimental data, but in that circumstances missing knowledge can be uncovered and gaps in the reconstruction can therefore be bridged leading to novel biological discoveries [3,4].

The GEMs that is designated as M-model does not differentiate between isozymes as such its predictive capability is not as accurate as that of ME model, which integrates metabolism and gene expression data. The construction of the former model (M-model) is relatively much easier, as the full protocol has been previously published [5], while the ME model requires additional expertise, as it integrates both metabolism, and gene expression data [6]. These two models could serve as platforms for construction of proof-of-principle strains. A number of proof-of-principle strains were constructed using E. coli GEMs for increasing succinic acid production [7-10] and/or other chemicals such as 1,-4 butanediol [11]. These strategies used GEMs that are considered M-models, with limited scope and fairly accurate predictive power. What we hope to see in the future is the of extended version of M-model that could include gene expression data (ME-model) in predicting proofof- concept studies that could be much more accurate predictive power that is greater than 80%. In conclusion, the M-models of E. coli has been extensively used for the construction of proof-ofconcept studies, particularly in increasing succinic acid production using a number of carbon sources, including glucose, and glycerol. Because of its limited scope and fair predictive accuracy, M-models are expected to be extended to ME-models for the construction of future proof-of-principle strains not limited to E. coli bacterium alone, but also for the forthcoming GEMs of microbial species with varieties of biotechnological applications in the field of medicine, agriculture, environment, industries and probably beyond.

References

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  3. O’Brien EJ, Monk JM, Palsson BO (2015) Using genome-scale models to predict biological capabilities. Cell 161(5): 971-987.
  4. Aziz RK, Khaw VL, Monk JM, Brunk E, Lewis R, et al. (2015) Model-driven discovery of synergistic inhibitors against E. coli and S. enterica serovar Typhimurium targeting a novel synthetic lethal pair, aldA and prpC. Front Microbiol 6: 958.
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  6. O’Brien EJ, Lerman JA, Chang RL, Hyduke DR, Palsson BØ (2013) Genome-scale models of metabolism and gene expression extend and refine growth phenotype prediction. Mol Syst Biol 9: 693-693.
  7. Mienda BS, MS Shamsir, Illias RM (2016) Model-guided metabolic gene knockout of gnd for enhanced succinate production in Escherichia coli from glucose and glycerol substrates. Comput Biol Chem 61: 130-137.
  8. Mienda BS, Shamsir MS, Illias R (2015) Model-aided atpE gene knockout strategy in Escherichia coli for enhanced succinic acid production from glycerol. J Biomol Struct Dyn 34(8): 1705-1716.
  9. Mienda BS, Shamsir MS, Illias R (2015) Model-assisted formate dehydrogenase-O (fdoH) gene knockout for enhanced succinate production in Escherichia coli from glucose and glycerol carbon sources. J Biomol Struct Dyn 34(11): 2305-2316.
  10. Lee SJ, Lee DY, Kim TY, Kim BH, Lee J, et al. (2005) Metabolic engineering of Escherichia coli for enhanced production of succinic acid, based on genome comparison and in silico gene knockout simulation. Appl Environ Microbiol 71(12): 7880-7887.
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