Sustainable production of chemicals from renewable non-food biomass has become a promising alternative to overcome environmental issues caused by our heavy dependence on fossil resources. Systems metabolic engineering, which integrates traditional metabolic engineering with systems biology, synthetic biology, and evolutionary engineering, is enabling the development of microbial cell factories capable of efficiently producing a myriad of chemicals and materials including biofuels, bulk and fine chemicals, polymers, amino acids, natural products and drugs. In this paper, many tools and strategies of systems metabolic engineering, including in silico genome-scale metabolic simulation, sophisticated enzyme engineering, optimal gene expression modulation, in vivo biosensors, de novo pathway design, and genomic engineering, employed for developing microbial cell factories are reviewed. Also, detailed procedures of systems metabolic engineering used to develop microbial strains producing chemicals and materials are showcased. Finally, future challenges and perspectives in further advancing systems metabolic engineering and establishing biorefineries are discussed.
The Essence of Metabolic Engineering. Review of Cellular Metabolism. Comprehensive Models for Cellular Reactions. Material Balances and Data Consistency. Regulation of Metabolic Pathways. Examples of Pathway Manipulations: Metabolic Engineering in Practice. Metabolic Pathway Synthesis. Metabolic Flux Analysis. Methods for the Experimental Determination of Metabolic Fluxes by Isotope Labeling. Applications of Metabolic Flux Analysis. Metabolic Control Analysis. Analysis of Structure of Metabolic Networks. Flux Analysis of Metabolic Networks. Thermodynamics of Cellular Processes. Glossary. Subject Index.
The traditional use of the yeast Saccharomyces cerevisiae in alcoholic fermentation has, over time, resulted in substantial accumulated knowledge concerning genetics, physiology, and biochemistry as well as genetic engineering and fermentation technologies. S. cerevisiae has become a platform organism for developing metabolic engineering strategies, methods, and tools. The current review discusses the relevance of several engineering strategies, such as rational and inverse metabolic engineering, evolutionary engineering, and global transcription machinery engineering, in yeast strain improvement. It also summarizes existing tools for fine-tuning and regulating enzyme activities and thus metabolic pathways. Recent examples of yeast metabolic engineering for food, beverage, and industrial biotechnology (bioethanol and bulk and fine chemicals) follow. S. cerevisiae currently enjoys increasing popularity as a production organism in industrial ("white") biotechnology due to its inherent tolerance of low pH values and high ethanol and inhibitor concentrations and its ability to grow anaerobically. Attention is paid to utilizing lignocellulosic biomass as a potential substrate.
Metabolic engineering emerged 20 years ago as the discipline occupied with the directed modification of metabolic pathways for the microbial synthesis of various products. As such, it deals with the engineering (design, construction, and optimization) of native as well as non-natural routes of product synthesis, aided in this task by the availability of synthetic DNA, the core enabling technology of synthetic biology. The two fields, however, only partially overlap in their interest in pathway engineering. While fabrication of biobricks, synthetic cells, genetic circuits, and nonlinear cell dynamics, along with pathway engineering, have occupied researchers in the field of synthetic biology, the sum total of these areas does not constitute a coherent definition of synthetic biology with a distinct intellectual foundation and well-defined areas of application. This paper reviews the origins of the two fields and advances two distinct paradigms for each of them: that of unit operations for metabolic engineering and electronic circuits for synthetic biology. In this context, metabolic engineering is about engineering cell factories for the biological manufacturing of chemical and pharmaceutical products, whereas the main focus of synthetic biology is fundamental biological research facilitated by the use of synthetic DNA and genetic circuits.
BACKGROUND: Through genetic engineering it is possible to introduce targeted genetic changes and hereby engineer the metabolism of microbial cells with the objective to obtain desirable phenotypes. However, owing to the complexity of metabolic networks, both in terms of structure and regulation, it is often difficult to predict the effects of genetic modifications on the resulting phenotype. Recently genome-scale metabolic models have been compiled for several different microorganisms where structural and stoichiometric complexity is inherently accounted for. New algorithms are being developed by using genome-scale metabolic models that enable identification of gene knockout strategies for obtaining improved phenotypes. However, the problem of finding optimal gene deletion strategy is combinatorial and consequently the computational time increases exponentially with the size of the problem, and it is therefore interesting to develop new faster algorithms. RESULTS: In this study we report an evolutionary programming based method to rapidly identify gene deletion strategies for optimization of a desired phenotypic objective function. We illustrate the proposed method for two important design parameters in industrial fermentations, one linear and other non-linear, by using a genome-scale model of the yeast Saccharomyces cerevisiae. Potential metabolic engineering targets for improved production of succinic acid, glycerol and vanillin are identified and underlying flux changes for the predicted mutants are discussed. CONCLUSION: We show that evolutionary programming enables solving large gene knockout problems in relatively short computational time. The proposed algorithm also allows the optimization of non-linear objective functions or incorporation of non-linear constraints and additionally provides a family of close to optimal solutions. The identified metabolic engineering strategies suggest that non-intuitive genetic modifications span several different pathways and may be necessary for solving challenging metabolic engineering problems.
BACKGROUND: Over the last few years a number of methods have been proposed for the phenotype simulation of microorganisms under different environmental and genetic conditions. These have been used as the basis to support the discovery of successful genetic modifications of the microbial metabolism to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications. RESULTS: OptFlux is an open-source and modular software aimed at being the reference computational application in the field. It is the first tool to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing metaheuristics or the previously proposed OptKnock algorithm. It also allows the use of stoichiometric metabolic models for (i) phenotype simulation of both wild-type and mutant organisms, using the methods of Flux Balance Analysis, Minimization of Metabolic Adjustment or Regulatory on/off Minimization of Metabolic flux changes, (ii) Metabolic Flux Analysis, computing the admissible flux space given a set of measured fluxes, and (iii) pathway analysis through the calculation of Elementary Flux Modes. OptFlux also contemplates several methods for model simplification and other pre-processing operations aimed at reducing the search space for optimization algorithms. The software supports importing/exporting to several flat file formats and it is compatible with the SBML standard. OptFlux has a visualization module that allows the analysis of the model structure that is compatible with the layout information of Cell Designer, allowing the superimposition of simulation results with the model graph. CONCLUSIONS: The OptFlux software is freely available, together with documentation and other resources, thus bridging the gap from research in strain optimization algorithms and the final users. It is a valuable platform for researchers in the field that have available a number of useful tools. Its open-source nature invites contributions by all those interested in making their methods available for the community. Given its plug-in based architecture it can be extended with new functionalities. Currently, several plug-ins are being developed, including network topology analysis tools and the integration with Boolean network based regulatory models.
Industrial biotechnology and microbial metabolic engineering are poised to help meet the growing demand for sustainable, low-cost commodity chemicals and natural products, yet the fraction of biochemicals amenable to commercial production remains limited. Common problems afflicting the current state-of-the-art include low volumetric productivities, build-up of toxic intermediates or products, and byproduct losses via competing pathways. To overcome these limitations, cell-free metabolic engineering (CFME) is expanding the scope of the traditional bioengineering model by using in vitro ensembles of catalytic proteins prepared from purified enzymes or crude lysates of cells for the production of target products. In recent years, the unprecedented level of control and freedom of design, relative to in vivo systems, has inspired the development of engineering foundations for cell-free systems. These efforts have led to activation of long enzymatic pathways (>8 enzymes), near theoretical conversion yields, productivities greater than 100 mg L(-1) h(-1) , reaction scales of >100 L, and new directions in protein purification, spatial organization, and enzyme stability. In the coming years, CFME will offer exciting opportunities to: (i) debug and optimize biosynthetic pathways; (ii) carry out design-build-test iterations without re-engineering organisms; and (iii) perform molecular transformations when bioconversion yields, productivities, or cellular toxicity limit commercial feasibility.
Besides its use for efficient production of recombinant proteins the methylotrophic yeast Pichia pastoris (syn. Komagataella spp.) has been increasingly employed as a platform to produce metabolites of varying origin. We summarize here the impressive methodological developments of the last years to model and analyze the metabolism of P. pastoris, and to engineer its genome and metabolic pathways. Efficient methods to insert, modify or delete genes via homologous recombination and CRISPR/Cas9, supported by modular cloning techniques, have been reported. An outstanding early example of metabolic engineering in P. pastoris was the humanization of protein glycosylation. More recently the cell metabolism was engineered also to enhance the productivity of heterologous proteins. The last few years have seen an increased number of metabolic pathway design and engineering in P. pastoris, mainly towards the production of complex (secondary) metabolites. In this review, we discuss the potential role of P. pastoris as a platform for metabolic engineering, its strengths, and major requirements for future developments of chassis strains based on synthetic biology principles.
Metabolic engineering has the potential to produce from simple, readily available, inexpensive starting materials a large number of chemicals that are currently derived from nonrenewable resources or limited natural resources. Microbial production of natural products has been achieved by transferring product-specific enzymes or entire metabolic pathways from rare or genetically intractable organisms to those that can be readily engineered, and production of unnatural specialty chemicals, bulk chemicals, and fuels has been enabled by combining enzymes or pathways from different hosts into a single microorganism and by engineering enzymes to have new function. Whereas existing production routes use well-known, safe, industrial microorganisms, future production schemes may include designer cells that are tailor-made for the desired chemical and production process. In any future, metabolic engineering will soon rival and potentially eclipse synthetic organic chemistry.
Amino-acid producers have traditionally been developed by repeated random mutagenesis owing to the difficulty in rationally engineering the complex and highly regulated metabolic network. Here, we report the development of the genetically defined L-threonine overproducing Escherichia coli strain by systems metabolic engineering. Feedback inhibitions of aspartokinase I and III (encoded by thrA and lysC, respectively) and transcriptional attenuation regulations (located in thrL) were removed. Pathways for Thr degradation were removed by deleting tdh and mutating ilvA. The metA and lysA genes were deleted to make more precursors available for Thr biosynthesis. Further target genes to be engineered were identified by transcriptome profiling combined with in silico flux response analysis, and their expression levels were manipulated accordingly. The final engineered E. coli strain was able to produce Thr with a high yield of 0.393 g per gram of glucose, and 82.4 g/l Thr by fed-batch culture. The systems metabolic engineering strategy reported here may be broadly employed for developing genetically defined organisms for the efficient production of various bioproducts.
The ecological footprint and economic performance of the current suite of biofuel production methods make them insufficient to displace fossil fuels and reduce their impact on the inventory of Green House Gas (GHG) in the global atmosphere. Algae metabolic engineering forms the basis for 4th generation biofuel production which can meet this need. The first generation biofuels are known to be made from agricultural products such as corn or sugarcane. The second generation biofuels use all forms of (lingo)cellulosic biomass. The third and fourth generation of biofuel production involves “algae-to-biofuels” technology: the former is basically processing of algae biomass for biofuel production, while the latter is about metabolic engineering of algae for producing biofuels from oxygenic photosynthetic microorganisms. Our review focuses on the research achievement of metabolic engineering of algae for biofuel production. It is concluded that 4th generation biofuel production has introduced the “cell factory” concept in this field, and shifted the research paradigm. There still exists several technical bottlenecks in algae biofuel research and development, which can only be solved by the use of post-genome tools on these photosynthetic organisms.
We present here a broad overview of the field of metabolic engineering, describing in the first section the key fundamental principles that define and distinguish it, as well as the technological and intellectual developments over the past approximately 20 years that have led to the current state of the art. Discussion of concepts such as metabolic flux analysis, metabolic control analysis, and rational and combinatorial methods is facilitated by illustrative examples of their application drawn from the extensive metabolic engineering literature. In the second section, we present some of the rapidly emerging technologies that we think will play pivotal roles in the continued growth of the field, from improving production metrics to expanding the range of attainable compounds.
Comprehensive knowledge regarding Saccharomyces cerevisiae has accumulated over time, and today S. cerevisiae serves as a widley used biotechnological production organism as well as a eukaryotic model system. The high transformation efficiency, in addition to the availability of the complete yeast genome sequence, has facilitated genetic manipulation of this microorganism, and new approaches are constantly being taken to metabolicially engineer this organism in order to suit specific needs. In this paper, strategies and concepts for metabolic engineering are discussed and several examples based upon selected studies involving S. cerevisiae are reviewed. The many different studies of metabolic engineering using this organism illustrate all the categories of this multidisciplinary field: extension of substrate range, improvements of producitivity and yield, elimination of byproduct formation, improvement of process performance, improvements of cellular properties, and extension of product range including heterologous protein production.
Natural products and their derivatives play an important role in modern healthcare as frontline treatments for many diseases and as inspiration for chemically synthesized therapeutics. With advances in sequencing and recombinant DNA technology, many of the biosynthetic pathways responsible for the production of these chemically complex yet valuable compounds have been elucidated. With an ever-expanding toolkit of biosynthetic components, metabolic engineering is an increasingly powerful method to improve natural product titers and generate novel compounds. Heterologous production platforms have enabled access to pathways from difficult to culture strains, systems biology and metabolic modeling tools have resulted in increasing predictive and analytic capabilities, advances in expression systems and regulation have enabled the fine-tuning of pathways for increased efficiency, and characterization of individual pathway components has facilitated the construction of hybrid pathways for the production of new compounds. These advances in the many aspects of metabolic engineering not only have yielded fascinating scientific discoveries but also make it an increasingly viable approach for the optimization of natural product biosynthesis.
Summary Plants synthesize an amazing diversity of volatile organic compounds ( VOC s) that facilitate interactions with their environment, from attracting pollinators and seed dispersers to protecting themselves from pathogens, parasites and herbivores. Recent progress in ‐omics technologies resulted in the isolation of genes encoding enzymes responsible for the biosynthesis of many volatiles and contributed to our understanding of regulatory mechanisms involved in VOC formation. In this review, we largely focus on the biosynthesis and regulation of plant volatiles, the involvement of floral volatiles in plant reproduction as well as their contribution to plant biodiversity and applications in agriculture via crop–pollinator interactions. In addition, metabolic engineering approaches for both the improvement of plant defense and pollinator attraction are discussed in light of methodological constraints and ecological complications that limit the transition of crops with modified volatile profiles from research laboratories to real‐world implementation. Contents Summary 16 I. Biosynthesis of volatile plant secondary metabolites and its interconnection with primary metabolism 16 II. Regulation of volatile emission in plants 22 III. Functions of plant volatile organic compounds 23 IV. Metabolic engineering of plant volatiles 25 V. Conclusions 27 Acknowledgements 28 References 28
Poly(3-hydroxyalkanoates) (PHAs) are a class of microbially produced polyesters that have potential applications as conventional plastics, specifically thermoplastic elastomers. A wealth of biological diversity in PHA formation exists, with at least 100 different PHA constituents and at least five different dedicated PHA biosynthetic pathways. This diversity, in combination with classical microbial physiology and modern molecular biology, has now opened up this area for genetic and metabolic engineering to develop optimal PHA-producing organisms. Commercial processes for PHA production were initially developed by W. R. Grace in the 1960s and later developed by Imperial Chemical Industries, Ltd., in the United Kingdom in the 1970s and 1980s. Since the early 1990s, Metabolix Inc. and Monsanto have been the driving forces behind the commercial exploitation of PHA polymers in the United States. The gram-negative bacterium Ralstonia eutropha, formerly known as Alcaligenes eutrophus, has generally been used as the production organism of choice, and intracellular accumulation of PHA of over 90% of the cell dry weight have been reported. The advent of molecular biological techniques and a developing environmental awareness initiated a renewed scientific interest in PHAs, and the biosynthetic machinery for PHA metabolism has been studied in great detail over the last two decades. Because the structure and monomeric composition of PHAs determine the applications for each type of polymer, a variety of polymers have been synthesized by cofeeding of various substrates or by metabolic engineering of the production organism. Classical microbiology and modern molecular bacterial physiology have been brought together to decipher the intricacies of PHA metabolism both for production purposes and for the unraveling of the natural role of PHAs. This review provides an overview of the different PHA biosynthetic systems and their genetic background, followed by a detailed summation of how this natural diversity is being used to develop commercially attractive, recombinant processes for the large-scale production of PHAs.
Abiotic stresses including drought, salinity, heat, cold, flooding, and ultraviolet radiation causes crop losses worldwide. In recent times, preventing these crop losses and producing more food and feed to meet the demands of ever-increasing human populations have gained unprecedented importance. However, the proportion of agricultural lands facing multiple abiotic stresses is expected only to rise under a changing global climate fueled by anthropogenic activities. Identifying the mechanisms developed and deployed by plants to counteract abiotic stresses and maintain their growth and survival under harsh conditions thus holds great significance. Recent investigations have shown that phytohormones, including the classical auxins, cytokinins, ethylene, and gibberellins, and newer members including brassinosteroids, jasmonates, and strigolactones may prove to be important metabolic engineering targets for producing abiotic stress-tolerant crop plants. In this review, we summarize and critically assess the roles that phytohormones play in plant growth and development and abiotic stress tolerance, besides their engineering for conferring abiotic stress tolerance in transgenic crops. We also describe recent successes in identifying the roles of phytohormones under stressful conditions. We conclude by describing the recent progress and future prospects including limitations and challenges of phytohormone engineering for inducing abiotic stress tolerance in crop plants.
MOTIVATION: The simulation of biochemical kinetic systems is a powerful approach that can be used for: (i) checking the consistency of a postulated model with a set of experimental measurements, (ii) answering 'what if?' questions and (iii) exploring possible behaviours of a model. Here we describe a generic approach to combine numerical optimization methods with biochemical kinetic simulations, which is suitable for use in the rational design of improved metabolic pathways with industrial significance (metabolic engineering) and for solving the inverse problem of metabolic pathways, i.e. the estimation of parameters from measured variables. RESULTS: We discuss the suitability of various optimization methods, focusing especially on their ability or otherwise to find global optima. We recommend that a suite of diverse optimization methods should be available in simulation software as no single one performs best for all problems. We describe how we have implemented such a simulation-optimization strategy in the biochemical kinetics simulator Gepasi and present examples of its application. AVAILABILITY: The new version of Gepasi (3.20), incorporating the methodology described here, is available on the Internet at http://gepasi.dbs.aber.ac.uk/softw/Gepasi. html. CONTACT: prm@aber.ac.uk
Application of recombinant DNA methods to restructure metabolic networks can improve production of metabolite and protein products by altering pathway distributions and rates. Recruitment of heterologous proteins enables extension of existing pathways to obtain new chemical products, alter posttranslational protein processing, and degrade recalcitrant wastes. Although some of the experimental and mathematical tools required for rational metabolic engineering are available, complex cellular responses to genetic perturbations can complicate predictive design.
Hypocrea jecorina (= Trichoderma reesei) is the main industrial source of cellulases and hemicellulases used to depolymerise plant biomass to simple sugars that are converted to chemical intermediates and biofuels, such as ethanol. Cellulases are formed adaptively, and several positive (XYR1, ACE2, HAP2/3/5) and negative (ACE1, CRE1) components involved in this regulation are now known. In addition, its complete genome sequence has been recently published, thus making the organism susceptible to targeted improvement by metabolic engineering. In this review, we summarise current knowledge about how cellulase biosynthesis is regulated, and outline recent approaches and suitable strategies for facilitating the targeted improvement of cellulase production by genetic engineering.