2010
DOI: 10.1002/bit.22996
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Evaluating Factors That Influence Microbial Synthesis Yields by Linear Regression with Numerical and Ordinal Variables

Abstract: In the production of chemicals via microbial fermentation, achieving a high yield is one of the most important objectives. We developed a statistical model to analyze influential factors that determine product yield by compiling data obtained from engineered Escherichia coli developed within last 10 years. Using both numerical and ordinal variables (e.g., enzymatic steps, cultivation conditions, and genetic modifications) as input parameters, our model revealed that cultivation modes, nutrient supplementation,… Show more

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Cited by 31 publications
(23 citation statements)
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“…Among the next-generation biofuels synthesized from pyruvate, IB possesses fewer reaction steps (5 reaction steps from pyruvate to IB) than the synthesis of 1-butanol or biodiesel. IB is less toxic to microbes (5), so it may achieve a higher product titer and yield (6,7). For example, a maximum titer of 50.8 g/liter of IB can be achieved in an engineered Escherichia coli strain (8).…”
mentioning
confidence: 99%
“…Among the next-generation biofuels synthesized from pyruvate, IB possesses fewer reaction steps (5 reaction steps from pyruvate to IB) than the synthesis of 1-butanol or biodiesel. IB is less toxic to microbes (5), so it may achieve a higher product titer and yield (6,7). For example, a maximum titer of 50.8 g/liter of IB can be achieved in an engineered Escherichia coli strain (8).…”
mentioning
confidence: 99%
“…Although these metabolic engineering strategies are effective in increasing the carbon flux toward the desired product, metabolic engineers cannot easily create “biofuel super bugs”. Extensive genetic modifications often increase metabolic burdens on the host and thus further interfere with cell growth and product synthesis (Colletti et al, 2011; Poust et al, 2014). For example, high copy number plasmids or strong promoter can place a heavy burden on the cell's growth and negatively affect productivity (Carrier et al, 1998; Jones et al, 2000).…”
Section: Metabolic Engineering Approaches For Biofuel Synthesismentioning
confidence: 99%
“…Systems biology knowledge will also make synthetic biology tools more reliable, enabling the precise control of transcription and translation regardless of the under-controlled gene (Mutalik et al, 2013). More powerful systems biology-based computational tools will simplify both the design and the optimization of synthetic metabolic pathways, improving titers and productivities (Colletti et al, 2011). Similarly, simplified genetic systems created in synthetic biology will provide systems biology with insight into the fundamentals of native gene regulation.…”
Section: Conclusion and Outlooksmentioning
confidence: 99%