Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942

Genome-scale metabolic network models for industrial microorganisms metabolic engineering: Current advances and future prospects

The construction of high-performance microbial cell factories (MCFs) is the centerpiece of biomanufacturing. However, the complex metabolic regulatory network of microorganisms poses great challenges for the efficient design and construction of MCFs. The genome-scale metabolic network models (GSMs) can systematically simulate the metabolic regulation process of microorganisms in silico, providing effective guidance for the rapid design and construction of MCFs. In this review, we summarized the development status of 16 important industrial microbial GSMs, and further outline the technologies or methods that continuously promote high-quality GSMs construction from five aspects: I) Databases and modeling tools facilitate GSMs reconstruction; II) evolving gap-filling technologies; III) constraint-based model reconstruction; IV) advances in algorithms; and V) developed visualization tools. In addition, we also summarized the applications of GSMs in guiding metabolic engineering from four aspects: I) exploring and explaining metabolic features; II) predicting the effects of genetic perturbations on metabolism; III) predicting the optimal phenotype; IV) guiding cell factories construction in practical experiment. Finally, we discussed the development of GSMs, aiming to provide a reference for efficiently reconstructing GSMs and guiding metabolic engineering.

Highlighting the potential of Synechococcus elongatus PCC 7942 as platform to produce α-linolenic acid through an updated genome-scale metabolic modeling

Cyanobacteria are prokaryotic organisms that capture energy from sunlight using oxygenic photosynthesis and transform CO2 into products of interest such as fatty acids. Synechococcus elongatus PCC 7942 is a model cyanobacterium efficiently engineered to accumulate high levels of omega-3 fatty acids. However, its exploitation as a microbial cell factory requires a better knowledge of its metabolism, which can be approached by using systems biology tools. To fulfill this objective, we worked out an updated, more comprehensive, and functional genome-scale model of this freshwater cyanobacterium, which was termed iMS837. The model includes 837 genes, 887 reactions, and 801 metabolites. When compared with previous models of S. elongatus PCC 7942, iMS837 is more complete in key physiological and biotechnologically relevant metabolic hubs, such as fatty acid biosynthesis, oxidative phosphorylation, photosynthesis, and transport, among others. iMS837 shows high accuracy when predicting growth performance and gene essentiality. The validated model was further used as a test-bed for the assessment of suitable metabolic engineering strategies, yielding superior production of non-native omega-3 fatty acids such as α-linolenic acid (ALA). As previously reported, the computational analysis demonstrated that fabF overexpression is a feasible metabolic target to increase ALA production, whereas deletion and overexpression of fabH cannot be used for this purpose. Flux scanning based on enforced objective flux, a strain-design algorithm, allowed us to identify not only previously known gene overexpression targets that improve fatty acid synthesis, such as Acetyl-CoA carboxylase and β-ketoacyl-ACP synthase I, but also novel potential targets that might lead to higher ALA yields. Systematic sampling of the metabolic space contained in iMS837 identified a set of ten additional knockout metabolic targets that resulted in higher ALA productions. In silico simulations under photomixotrophic conditions with acetate or glucose as a carbon source boosted ALA production levels, indicating that photomixotrophic nutritional regimens could be potentially exploited in vivo to improve fatty acid production in cyanobacteria. Overall, we show that iMS837 is a powerful computational platform that proposes new metabolic engineering strategies to produce biotechnologically relevant compounds, using S. elongatus PCC 7942 as non-conventional microbial cell factory.

Reconstruction of a regulated two-cell metabolic model to study biohydrogen production in a diazotrophic cyanobacterium Anabaena variabilis ATCC 29413

Anabaena variabilis is a diazotrophic filamentous cyanobacterium that differentiates to heterocysts and produces hydrogen as a byproduct. Study on metabolic interactions of the two differentiated cells provides a better understanding of its metabolism especially for improving hydrogen production. To this end, a genome-scale metabolic model for Anabaena variabilis ATCC 29413, iAM957, was reconstructed and evaluated in this research. Then, the model and transcriptomic data of the vegetative and heterocyst cells were applied to construct a regulated two-cell metabolic model. The regulated model improved prediction for biomass in high radiation levels. The regulated model predicts that heterocysts provide an oxygen-free environment and then, this model was used to find strategies for improving hydrogen production in heterocysts. The predictions indicate that the removal of uptake hydrogenase improves hydrogen production which is consistent with previous empirical research. Furthermore, the regulated model proposed activation of some reactions to provide redox cofactors which are required for improving hydrogen production up to 60% by bidirectional hydrogenase.

Applications of stable isotope-based metabolomics and fluxomics toward synthetic biology of cyanobacteria

Unique features of cyanobacteria (e.g., photosynthesis and nitrogen fixation) make them potential candidates for production of biofuels and other value-added biochemicals. As prokaryotes, they can be readily engineered using synthetic and systems biology tools. Metabolic engineering of cyanobacteria for the synthesis of desired compounds requires in-depth knowledge of central carbon and nitrogen metabolism, pathway fluxes, and their regulation. Metabolomics and fluxomics offer the comprehensive analysis of metabolism by directly characterizing the biochemical activities of cells. This information is acquired by measuring the abundance of key metabolites and their rates of interconversion, which can be achieved by labeling cells with stable isotopes, quantifying metabolite pool sizes and isotope incorporation by gas chromatography/liquid chromatography-mass spectrometry GC/LC-MS or nuclear magnetic resonance (NMR), and mathematical modeling to estimate in vivo metabolic fluxes. Herein, we review progress that has been made to adapt metabolomics and fluxomics tools to examine model cyanobacterial species. We summarize the application of metabolic flux analysis (MFA) strategies to identify metabolic bottlenecks that can be targeted to boost cell growth, improve stress tolerance, or enhance biochemical production in cyanobacteria. Despite the advances in metabolomics, fluxomics, and other synthetic and systems biology tools during the past years, further efforts are required to increase our understanding of cyanobacterial metabolism in order to create efficient photosynthetic hosts for the production of value-added compounds. This article is categorized under: Laboratory Methods and Technologies > Metabolomics Biological Mechanisms > Metabolism Analytical and Computational Methods > Analytical Methods.

Emerging Species and Genome Editing Tools: Future Prospects in Cyanobacterial Synthetic Biology

Recent advances in synthetic biology and an emerging algal biotechnology market have spurred a prolific increase in the availability of molecular tools for cyanobacterial research. Nevertheless, work to date has focused primarily on only a small subset of model species, which arguably limits fundamental discovery and applied research towards wider commercialisation. Here, we review the requirements for uptake of new strains, including several recently characterised fast-growing species and promising non-model species. Furthermore, we discuss the potential applications of new techniques available for transformation, genetic engineering and regulation, including an up-to-date appraisal of current Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR associated protein (CRISPR/Cas) and CRISPR interference (CRISPRi) research in cyanobacteria. We also provide an overview of several exciting molecular tools that could be ported to cyanobacteria for more advanced metabolic engineering approaches (e.g., genetic circuit design). Lastly, we introduce a forthcoming mutant library for the model species Synechocystis sp. PCC 6803 that promises to provide a further powerful resource for the cyanobacterial research community.

State-of-the-Art Genetic Modalities to Engineer Cyanobacteria for Sustainable Biosynthesis of Biofuel and Fine-Chemicals to Meet Bio-Economy Challenges

In recent years, metabolic engineering of microorganisms has attained much research interest to produce biofuels and industrially pertinent chemicals. Owing to the relatively fast growth rate, genetic malleability, and carbon neutral production process, cyanobacteria has been recognized as a specialized microorganism with a significant biotechnological perspective. Metabolically engineering cyanobacterial strains have shown great potential for the photosynthetic production of an array of valuable native or non-native chemicals and metabolites with profound agricultural and pharmaceutical significance using CO₂ as a building block. In recent years, substantial improvements in developing and introducing novel and efficient genetic tools such as genome-scale modeling, high throughput omics analyses, synthetic/system biology tools, metabolic flux analysis and clustered regularly interspaced short palindromic repeats (CRISPR)-associated nuclease (CRISPR/cas) systems have been made for engineering cyanobacterial strains. Use of these tools and technologies has led to a greater understanding of the host metabolism, as well as endogenous and heterologous carbon regulation mechanisms which consequently results in the expansion of maximum productive ability and biochemical diversity. This review summarizes recent advances in engineering cyanobacteria to produce biofuel and industrially relevant fine chemicals of high interest. Moreover, the development and applications of cutting-edge toolboxes such as the CRISPR-cas9 system, synthetic biology, high-throughput "omics", and metabolic flux analysis to engineer cyanobacteria for large-scale cultivation are also discussed.

New Applications of Synthetic Biology Tools for Cyanobacterial Metabolic Engineering

Cyanobacteria are promising microorganisms for sustainable biotechnologies, yet unlocking their potential requires radical re-engineering and application of cutting-edge synthetic biology techniques. In recent years, the available devices and strategies for modifying cyanobacteria have been increasing, including advances in the design of genetic promoters, ribosome binding sites, riboswitches, reporter proteins, modular vector systems, and markerless selection systems. Because of these new toolkits, cyanobacteria have been successfully engineered to express heterologous pathways for the production of a wide variety of valuable compounds. Cyanobacterial strains with the potential to be used in real-world applications will require the refinement of genetic circuits used to express the heterologous pathways and development of accurate models that predict how these pathways can be best integrated into the larger cellular metabolic network. Herein, we review advances that have been made to translate synthetic biology tools into cyanobacterial model organisms and summarize experimental and in silico strategies that have been employed to increase their bioproduction potential. Despite the advances in synthetic biology and metabolic engineering during the last years, it is clear that still further improvements are required if cyanobacteria are to be competitive with heterotrophic microorganisms for the bioproduction of added-value compounds.

Metabolic engineering of Synechococcus elongatus PCC 7942 for improvement of 1,3-propanediol and glycerol production based on in silico simulation of metabolic flux distribution

Background

Production directly from carbon dioxide by engineered cyanobacteria is one of the promising technologies for sustainable future. Previously, we have successfully achieved 1,3-propanediol (1,3-PDO) production using Synechococcus elongatus PCC 7942 with a synthetic metabolic pathway. The strain into which the synthetic metabolic pathway was introduced produced 3.48 mM (0.265 g/L) 1,3-PDO and 14.3 mM (1.32 g/L) glycerol during 20 days of incubation. In this study, the productivities of 1,3-PDO were improved by gene disruption selected by screening with in silico simulation.

Methods

First, a stoichiometric metabolic model was applied to prediction of cellular metabolic flux distribution in a 1,3-PDO-producing strain of S. elongatus PCC 7942. A genome-scale model of S. elongatus PCC 7942 constructed by Knoop was modified by the addition of a synthetic metabolic pathway for 1,3-PDO production. Next, the metabolic flux distribution predicted by metabolic flux balance analysis (FBA) was used for in silico simulation of gene disruption. As a result of gene disruption simulation, NADPH dehydrogenase 1 (NDH-1) complexes were found by screening to be the most promising candidates for disruption to improve 1,3-PDO production. The effect of disruption of the gene encoding a subunit of the NDH-1 complex was evaluated in the 1,3-PDO-producing strain.

Results and Conclusions

During 20 days of incubation, the ndhF1-null 1,3-PDO-producing strain showed the highest titers: 4.44 mM (0.338 g/L) 1,3-PDO and 30.3 mM (2.79 g/L) glycerol. In this study, we successfully improved 1,3-PDO productivity on the basis of in silico simulation of gene disruption.

Electronic supplementary material

The online version of this article (10.1186/s12934-017-0824-4) contains supplementary material, which is available to authorized users.

The use of genome-scale metabolic network reconstruction to predict fluxes and equilibrium composition of N-fixing versus C-fixing cells in a diazotrophic cyanobacterium, Trichodesmium erythraeum

Background

Computational, genome based predictions of organism phenotypes has enhanced the ability to investigate the biological phenomena that help organisms survive and respond to their environments. In this study, we have created the first genome-scale metabolic network reconstruction of the nitrogen fixing cyanobacterium T. erythraeum and used genome-scale modeling approaches to investigate carbon and nitrogen fluxes as well as growth and equilibrium population composition.

Results

We created a genome-scale reconstruction of T. erythraeum with 971 reactions, 986 metabolites, and 647 unique genes. We then used data from previous studies as well as our own laboratory data to establish a biomass equation and two distinct submodels that correspond to the two cell types formed by T. erythraeum. We then use flux balance analysis and flux variability analysis to generate predictions for how metabolism is distributed to account for the unique productivity of T. erythraeum. Finally, we used in situ data to constrain the model, infer time dependent population compositions and metabolite production using dynamic Flux Balance Analysis. We find that our model predicts equilibrium compositions similar to laboratory measurements, approximately 15.5% diazotrophs for our model versus 10-20% diazotrophs reported in literature. We also found that equilibrium was the most efficient mode of growth and that equilibrium was stoichiometrically mediated. Moreover, the model predicts that nitrogen leakage is an essential condition of optimality for T. erythraeum; cells leak approximately 29.4% total fixed nitrogen when growing at the optimal growth rate, which agrees with values observed in situ.

Conclusion

The genome-metabolic network reconstruction allows us to use constraints based modeling approaches to predict growth and optimal cellular composition in T. erythraeum colonies. Our predictions match both in situ and laboratory data, indicating that stoichiometry of metabolic reactions plays a large role in the differentiation and composition of different cell types. In order to realize the full potential of the model, advance modeling techniques which account for interactions between colonies, the environment and surrounding species need to be developed.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0383-z) contains supplementary material, which is available to authorized users.

Algal Cell Factories: Approaches, Applications, and Potentials

With the advent of modern biotechnology, microorganisms from diverse lineages have been used to produce bio-based feedstocks and bioactive compounds. Many of these compounds are currently commodities of interest, in a variety of markets and their utility warrants investigation into improving their production through strain development. In this review, we address the issue of strain improvement in a group of organisms with strong potential to be productive “cell factories”: the photosynthetic microalgae. Microalgae are a diverse group of phytoplankton, involving polyphyletic lineage such as green algae and diatoms that are commonly used in the industry. The photosynthetic microalgae have been under intense investigation recently for their ability to produce commercial compounds using only light, CO₂, and basic nutrients. However, their strain improvement is still a relatively recent area of work that is under development. Importantly, it is only through appropriate engineering methods that we may see the full biotechnological potential of microalgae come to fruition. Thus, in this review, we address past and present endeavors towards the aim of creating productive algal cell factories and describe possible advantageous future directions for the field.

Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. Here, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology.

Cyanobacteria as Chassis for Industrial Biotechnology: Progress and Prospects

Cyanobacteria hold significant potential as industrial biotechnology (IB) platforms for the production of a wide variety of bio-products ranging from biofuels such as hydrogen, alcohols and isoprenoids, to high-value bioactive and recombinant proteins. Underpinning this technology, are the recent advances in cyanobacterial “omics” research, the development of improved genetic engineering tools for key species, and the emerging field of cyanobacterial synthetic biology. These approaches enabled the development of elaborate metabolic engineering programs aimed at creating designer strains tailored for different IB applications. In this review, we provide an overview of the current status of the fields of cyanobacterial omics and genetic engineering with specific focus on the current molecular tools and technologies that have been developed in the past five years. The paper concludes by giving insights on future commercial applications of cyanobacteria and highlights the challenges that need to be addressed in order to make cyanobacterial industrial biotechnology more feasible in the near future.

Cyanobacterial Biofuels: Strategies and Developments on Network and Modeling

Cyanobacteria, the phototrophic microorganisms, have attracted much attention recently as a promising source for environmentally sustainable biofuels production. However, barriers for commercial markets of cyanobacteria-based biofuels concern the economic feasibility. Miscellaneous strategies for improving the production performance of cyanobacteria have thus been developed. Among these, the simple ad hoc strategies resulting in failure to optimize fully cell growth coupled with desired product yield are explored. With the advancement of genomics and systems biology, a new paradigm toward systems metabolic engineering has been recognized. In particular, a genome-scale metabolic network reconstruction and modeling is a crucial systems-based tool for whole-cell-wide investigation and prediction. In this review, the cyanobacterial genome-scale metabolic models, which offer a system-level understanding of cyanobacterial metabolism, are described. The main process of metabolic network reconstruction and modeling of cyanobacteria are summarized. Strategies and developments on genome-scale network and modeling through the systems metabolic engineering approach are advanced and employed for efficient cyanobacterial-based biofuels production.

Advances in Metabolic Engineering of Cyanobacteria for Photosynthetic Biochemical Production

Engineering cyanobacteria into photosynthetic microbial cell factories for the production of biochemicals and biofuels is a promising approach toward sustainability. Cyanobacteria naturally grow on light and carbon dioxide, bypassing the need of fermentable plant biomass and arable land. By tapping into the central metabolism and rerouting carbon flux towards desirable compound production, cyanobacteria are engineered to directly convert CO₂ into various chemicals. This review discusses the diversity of bioproducts synthesized by engineered cyanobacteria, the metabolic pathways used, and the current engineering strategies used for increasing their titers.