Strategies for systems‐level metabolic engineering

Abstract

Bio-based production of chemicals, fuels and materials is becoming more and more important due to the increasing environmental problems and sharply increasing oil price. To make these biobased processes economically competitive, the biotechnology industry explores new ways to improve the performance of microbial strains in fermentation processes. In contrast to the random mutagenesis and/or intuitive local metabolic engineering practiced in the past, we are now moving towards global-scale metabolic engineering, aided by various experimental and computational tools. This has recently led to some remarkable achievements for the overproduction of valueadded products. In this review, we highlight several relevant gene manipulation tools and computational tools using genome-scale stoichiometric models, and provide useful strategies for successful metabolic engineering along with selected exemplary studies.

Genome‐scale metabolic model of methylotrophic yeast Pichia pastoris and its use for in silico analysis of heterologous protein production

“…Use of the genome-scale metabolic models has enabled designing strategies for increasing the production of target compounds [1], such as nutritional supplements [2] and biofuels [3]. Metabolic models have also been utilized for identifying targets for new drugs against pathogenic microorganisms [4], and have been useful in dis-covering new information on the biological systems that they represent.…”

Increased Malonyl Coenzyme A Biosynthesis by Tuning the Escherichia coli Metabolic Network and Its Application to Flavanone Production

“…This limitation is generally addressed through modifications based on ad hoc predictions or random genetic perturbations, often overlooking the myriad of interactions within the global metabolic network. Advances in computational systems biology have yielded more systems-based approaches (8,17,37,38), providing a means to analyze genome-wide reaction networks using limited parameters and assumptions (19,25,35). Using constraints developed from the network architecture to define a metabolic flux space and optimizing these by means of a prescribed metabolic objective, such as biomass, known as flux balance analysis (FBA) (39), one can explore unique aspects within the solution space (30).…”

A systems approach to traditional oriental medicine

“…The multicomponent/multitargeting principle of TOM, which aims to sustain the healthy status of the human body in its entirety, is very compatible with the holistic view of systems biology, which considers interactions among components (e.g., genes, RNAs, proteins, metabolites and metabolic fluxes) at various levels and networks in a given biological system 6,31 . For example, network-based approaches of systems biology will provide additional insights on the compounds in TOM by linking them with their targets at the whole metabolic and regulatory network level using high-throughput techniques, which will consequently allow us to predict more effective synergistic compounds 32 .…”