Experimental evolution and gene knockout studies reveal AcrA-mediated isobutanol tolerance in Ralstonia eutropha

Recent advances in synthetic biology toolkits and metabolic engineering of Ralstonia eutropha H16 for production of value-added chemicals

Ralstonia eutropha H16, a facultative chemolithoautotrophic Gram-negative bacterium, demonstrates remarkable metabolic flexibility by utilizing either diverse organic substrates or CO2 as the sole carbon source, with H2 serving as the electron donor under aerobic conditions. The capacity of carbon and energy metabolism of R. eutropha H16 enabled development of synthetic biology technologies and strategies to engineer its metabolism for biosynthesis of value-added chemicals. This review firstly outlines the development of synthetic biology tools tailored for R. eutropha H16, including construction of expression vectors, regulatory elements, and transformation techniques. The availability of comprehensive omics data (i.e., transcriptomic, proteomic, and metabolomic) combined with the fully annotated genome sequence provides a robust genetic framework for advanced metabolic engineering. These advancements facilitate efficient reprogramming metabolic network of R. eutropha. The potential of R. eutropha as a versatile microbial platform for industrial biotechnology is further underscored by its ability to utilize a wide range of carbon sources for the production of value-added chemicals through both autotrophic and heterotrophic pathways. The integration of state-of-the-art genetic and genomic engineering tools and strategies with high cell-density fermentation processes enables engineered R. eutropha as promising microbial cell factories for optimizing carbon fluxes and expanding the portfolio of bio-based products.

Microbial host engineering for sustainable isobutanol production from renewable resources

Due to the limited resources and environmental problems associated with fossil fuels, there is a growing interest in utilizing renewable resources for the production of biofuels through microbial fermentation. Isobutanol is a promising biofuel that could potentially replace gasoline. However, its production efficiency is currently limited by the use of naturally isolated microorganisms. These naturally isolated microorganisms often encounter problems such as a limited range of substrates, low tolerance to solvents or inhibitors, feedback inhibition, and an imbalanced redox state. This makes it difficult to improve their production efficiency through traditional process optimization methods. Fortunately, recent advancements in genetic engineering technologies have made it possible to enhance microbial hosts for the increased production of isobutanol from renewable resources. This review provides a summary of the strategies and synthetic biology approaches that have been employed in the past few years to improve naturally isolated or non-natural microbial hosts for the enhanced production of isobutanol by utilizing different renewable resources. Furthermore, it also discusses the challenges that are faced by engineered microbial hosts and presents future perspectives to enhancing isobutanol production. KEY POINTS: • Promising potential of isobutanol to replace gasoline • Engineering of native and non-native microbial host for isobutanol production • Challenges and opportunities for enhanced isobutanol production.

Synthetic biology toolkit of Ralstonia eutropha (Cupriavidus necator)

Synthetic biology encompasses many kinds of ideas and techniques with the common theme of creating something novel. The industrially relevant microorganism, Ralstonia eutropha (also known as Cupriavidus necator), has long been a subject of metabolic engineering efforts to either enhance a product it naturally makes (polyhydroxyalkanoate) or produce novel bioproducts (e.g., biofuels and other small molecule compounds). Given the metabolic versatility of R. eutropha and the existence of multiple molecular genetic tools and techniques for the organism, development of a synthetic biology toolkit is underway. This toolkit will allow for novel, user-friendly design that can impart new capabilities to R. eutropha strains to be used for novel application. This article reviews the different synthetic biology techniques currently available for modifying and enhancing bioproduction in R. eutropha. KEY POINTS: • R. eutropha (C. necator) is a versatile organism that has been examined for many applications. • Synthetic biology is being used to design more powerful strains for bioproduction. • A diverse synthetic biology toolkit is being developed to enhance R. eutropha's capabilities.

Synthetic biology toolkit for engineering Cupriviadus necator H16 as a platform for CO2 valorization

BACKGROUND

CO₂ valorization is one of the effective methods to solve current environmental and energy problems, in which microbial electrosynthesis (MES) system has proved feasible and efficient. Cupriviadus necator (Ralstonia eutropha) H16, a model chemolithoautotroph, is a microbe of choice for CO₂ conversion, especially with the ability to be employed in MES due to the presence of genes encoding [NiFe]-hydrogenases and all the Calvin-Benson-Basham cycle enzymes. The CO₂ valorization strategy will make sense because the required hydrogen can be produced from renewable electricity independently of fossil fuels.

MAIN BODY

In this review, synthetic biology toolkit for C. necator H16, including genetic engineering vectors, heterologous gene expression elements, platform strain and genome engineering, and transformation strategies, is firstly summarized. Then, the review discusses how to apply these tools to make C. necator H16 an efficient cell factory for converting CO₂ to value-added products, with the examples of alcohols, fatty acids, and terpenoids. The review is concluded with the limitation of current genetic tools and perspectives on the development of more efficient and convenient methods as well as the extensive applications of C. necator H16.

CONCLUSIONS

Great progress has been made on genetic engineering toolkit and synthetic biology applications of C. necator H16. Nevertheless, more efforts are expected in the near future to engineer C. necator H16 as efficient cell factories for the conversion of CO₂ to value-added products.

Cell-free production of isobutanol: A completely immobilized system

A completely immobilized cell-free enzyme reaction system was used to convert ketoisovaleric acid to isobutanol, a desirable biofuel, with a molar yield of 43% and a titer of 2 g/L, which are comparable to high performing in vivo systems (e.g. 41% and 5.4 g/L, respectively, for Clostridium thermocellum). The approach utilizes, for the first time, a series of previously reported enzyme mutants that either overproduce the product or are more stable when compared with their wild type. The selected enzyme variants include keto-acid decarboxylase attached to a maltose binding protein, alcohol dehydrogenase, and formate dehydrogenase. These enzymes were screened for thermal, pH, and product stability to choose optima for this system which were pH 7.4 and 35 °C. This system is designed to address well-known limitations of in vivo systems such as low product concentrations due to product feedback inhibition, instability of cells, and lack of economic product recovery.

Techniques for enhancing the tolerance of industrial microbes to abiotic stresses: A review

The diversity of stress responses and survival strategies evolved by microorganism enables them to survive and reproduce in a multitude of harsh environments, whereas the discovery of the underlying resistance genes or mechanisms laid the foundation for the directional enhancement of microbial tolerance to abiotic stresses encountered in industrial applications. Many biological techniques have been developed for improving the stress resistance of industrial microorganisms, which greatly benefited the bacteria on which industrial production is based. This review introduces the main techniques for enhancing the resistance of microorganisms to abiotic stresses, including evolutionary engineering, metabolic engineering, and process engineering, developed in recent years. In addition, we also discuss problems that are still present in this area and offer directions for future research.

Network-Based Identification of Adaptive Pathways in Evolved Ethanol-Tolerant Bacterial Populations

Efficient production of ethanol for use as a renewable fuel requires organisms with a high level of ethanol tolerance. However, this trait is complex and increased tolerance therefore requires mutations in multiple genes and pathways. Here, we use experimental evolution for a system-level analysis of adaptation of Escherichia coli to high ethanol stress. As adaptation to extreme stress often results in complex mutational data sets consisting of both causal and noncausal passenger mutations, identifying the true adaptive mutations in these settings is not trivial. Therefore, we developed a novel method named IAMBEE (Identification of Adaptive Mutations in Bacterial Evolution Experiments). IAMBEE exploits the temporal profile of the acquisition of mutations during evolution in combination with the functional implications of each mutation at the protein level. These data are mapped to a genome-wide interaction network to search for adaptive mutations at the level of pathways. The 16 evolved populations in our data set together harbored 2,286 mutated genes with 4,470 unique mutations. Analysis by IAMBEE significantly reduced this number and resulted in identification of 90 mutated genes and 345 unique mutations that are most likely to be adaptive. Moreover, IAMBEE not only enabled the identification of previously known pathways involved in ethanol tolerance, but also identified novel systems such as the AcrAB-TolC efflux pump and fatty acids biosynthesis and even allowed to gain insight into the temporal profile of adaptation to ethanol stress. Furthermore, this method offers a solid framework for identifying the molecular underpinnings of other complex traits as well.

Rearrangement of Coenzyme A-Acylated Carbon Chain Enables Synthesis of Isobutanol via a Novel Pathway in Ralstonia eutropha

Coenzyme A (CoA)-dependent pathways have been explored extensively for the biosynthesis of fuels and chemicals. While CoA-dependent mechanisms are widely used to elongate carbon chains in a linear fashion, branch-making chemistry has not been incorporated. In this study, we demonstrated the production of isobutanol, a branched-chain alcohol that can be used as a gasoline substitute, using a novel CoA-dependent pathway in recombinant Ralstonia eutropha H16. The designed pathway is constituted of three modules: chain elongation, rearrangement, and modification. We first integrated and optimized the chain elongation and modification modules, and we achieved the production of ∼200 mg/L n-butanol from fructose or ∼30 mg/L from formate by engineered R. eutropha. Subsequently, we incorporated the rearrangement module, which features a previously uncharacterized, native isobutyryl-CoA mutase in R. eutropha. The engineered strain produced ∼30 mg/L isobutanol from fructose. The carbon skeleton rearrangement chemistry demonstrated here may be used to expand the range of the chemicals accessible with CoA-dependent pathways.

Comparative analysis of L-sorbose dehydrogenase by docking strategy for 2-keto-L-gulonic acid production in Ketogulonicigenium vulgare and Bacillus endophyticus consortium

Improving the yield of 2-keto-L-gulonic acid (2-KGA), the direct precursor of vitamin C, draws more and more attention in industrial production. In this study, we try to increase the 2-KGA productivity by computer-aided selection of genes encoding L-sorbose dehydrogenases (SDH) of Ketogulonicigenium vulgare. First, six SDHs were modeled by docking strategy to predict the binding mode with co-factor PQQ. The binding energy between SSDA1-H/SSDA1-L and PQQ was the highest, followed by SSDA3/SSDA2. The binding energy between SSDA1-P/SSDB and PQQ was the lowest. Then, these genes were overexpressed, respectively, in an industrial strain K. vulgare HKv604. Overexpression of ssda1-l and ssda1-h enhanced the 2-KGA production by 7.89 and 12.56 % in mono-cultured K. vulgare, and by 13.21 and 16.86 % when K. vulgare was co-cultured with Bacillus endophyticus. When the engineered K. vulgare SyBE_Kv000116013 (overexpression of ssda1-p) or SyBE_Kv000116016 (overexpression of ssdb) was co-cultured with B. endophyticus, the 2-KGA production decreased significantly. The docking results were in accordance with the experimental data, which indicated that computer-aided modeling is an efficient strategy for screening more efficient enzymes.