Strategies and challenges for metabolic rewiring

"Metabolic burden" explained: stress symptoms and its related responses induced by (over)expression of (heterologous) proteins in Escherichia coli

BACKGROUND

Engineering bacterial strains to redirect the metabolism towards the production of a specific product has enabled the development of industrial biotechnology. However, rewiring the metabolism can have severe implications for a microorganism, rendering cells with stress symptoms such as a decreased growth rate, impaired protein synthesis, genetic instability and an aberrant cell size. On an industrial scale, this is reflected in processes that are not economically viable.

MAIN TEXT

In literature, most stress symptoms are attributed to "metabolic burden", however the actual triggers and stress mechanisms involved are poorly understood. Therefore, in this literature review, we aimed to get a better insight in how metabolic engineering affects Escherichia coli and link the observed stress symptoms to its cause. Understanding the possible implications that chosen engineering strategies have, will help to guide the reader towards optimising the envisioned process more efficiently.

CONCLUSION

This review addresses the gap in literature and discusses the triggers and effects of stress mechanisms that can be activated when (over)expressing (heterologous) proteins in Escherichia coli. It uncovers that the activation of the different stress mechanisms is complex and that many are interconnected. The reader is shown that care has to be taken when (over)expressing (heterologous) proteins as the cell's metabolism is tightly regulated.

Global Cellular Metabolic Rewiring Adapts Corynebacterium glutamicum to Efficient Nonnatural Xylose Utilization

Xylose, the major component of lignocellulosic biomass, cannot be naturally or efficiently utilized by most microorganisms. Xylose (co)utilization is considered a cornerstone of efficient lignocellulose-based biomanufacturing. We evolved a rapidly xylose-utilizing strain, Cev2-18-5, which showed the highest reported specific growth rate (0.357 h^-1) on xylose among plasmid-free Corynebacterium glutamicum strains. A genetically clear chassis strain, CGS15, was correspondingly reconstructed with an efficient glucose-xylose coutilization performance based on comparative genomic analysis and mutation reconstruction. With the introduction of a succinate-producing plasmid, the resulting strain, CGS15-SA1, can efficiently produce 97.1 g/L of succinate with an average productivity of 8.09 g/L/h by simultaneously utilizing glucose and xylose from corn stalk hydrolysate. We further revealed a novel xylose regulatory mechanism mediated by the endogenous transcription factor IpsA with global regulatory effects on C. glutamicum. A synergistic effect on carbon metabolism and energy supply, motivated by three genomic mutations (P_sod(C131T)-xylAB, P_tuf(Δ21)-araE, and ipsA^C331T), was found to endow C. glutamicum with the efficient xylose utilization and rapid growth phenotype. Overall, this work not only provides promising C. glutamicum chassis strains for a lignocellulosic biorefinery but also enriches the understanding of the xylose regulatory mechanism. IMPORTANCE A novel xylose regulatory mechanism mediated by the transcription factor IpsA was revealed. A synergistic effect on carbon metabolism and energy supply was found to endow C. glutamicum with the efficient xylose utilization and rapid growth phenotype. The new xylose regulatory mechanism enriches the understanding of nonnatural substrate metabolism and encourages exploration new engineering targets for rapid xylose utilization. This work also provides a paradigm to understand and engineer the metabolism of nonnatural renewable substrates for sustainable biomanufacturing.

Combinatorial Metabolic Engineering Strategies for the Enhanced Production of Free Fatty Acids in Escherichia coli

In this study, we evaluated the effects of several metabolic engineering strategies in a systematic and combinatorial manner to enhance the free fatty acid (FFA) production in Escherichia coli. The strategies included (i) overexpression of mutant thioesterase I ('TesA^R64C) to efficiently release the FFAs from fatty acyl-ACP; (ii) coexpression of global regulatory protein FadR; (iii) heterologous expression of methylmalonyl-CoA carboxyltransferase and phosphoenolpyruvate carboxylase to synthesize fatty acid precursor molecule malonyl-CoA; and (iv) disruption of genes associated with membrane proteins (GusC, MdlA, and EnvR) to improve the cellular state and export the FFAs outside the cell. The synergistic effects of these genetic modifications in strain SBF50 yielded 7.2 ± 0.11 g/L FFAs at the shake flask level. In fed-batch cultivation under nitrogen-limiting conditions, strain SBF50 produced 33.6 ± 0.02 g/L FFAs with a productivity of 0.7 g/L/h from glucose, which is the maximum titer reported in E. coli to date. Combinatorial metabolic engineering approaches can prove to be highly useful for the large-scale production of FA-derived chemicals and fuels.

Metabolic reconfiguration enables synthetic reductive metabolism in yeast

Cell proliferation requires the integration of catabolic processes to provide energy, redox power and biosynthetic precursors. Here we show how the combination of rational design, metabolic rewiring and recombinant expression enables the establishment of a decarboxylation cycle in the yeast cytoplasm. This metabolic cycle can support growth by supplying energy and increased provision of NADPH or NADH in the cytosol, which can support the production of highly reduced chemicals such as glycerol, succinate and free fatty acids. With this approach, free fatty acid yield reached 40% of theoretical yield, which is the highest yield reported for Saccharomyces cerevisiae to our knowledge. This study reports the implementation of a synthetic decarboxylation cycle in the yeast cytosol, and its application in achieving high yields of valuable chemicals in cell factories. Our study also shows that, despite extensive regulation of catabolism in yeast, it is possible to rewire the energy metabolism, illustrating the power of biodesign.

Optimizing microbial networks through metabolic bypasses

Metabolism has long been considered as a relatively stiff set of biochemical reactions. This somewhat outdated and dogmatic view has been challenged over the last years, as multiple studies exposed unprecedented plasticity of metabolism by exploring rational and evolutionary modifications within the metabolic network of cell factories. Of particular importance is the emergence of metabolic bypasses, which consist of enzymatic reaction(s) that support unnatural connections between metabolic nodes. Such novel topologies can be generated through the introduction of heterologous enzymes or by upregulating native enzymes (sometimes relying on promiscuous activities thereof). Altogether, the adoption of bypasses resulted in an expansion in the capacity of the host's metabolic network, which can be harnessed for bioproduction. In this review, we discuss modifications to the canonical architecture of central carbon metabolism derived from such bypasses towards six optimization purposes: stoichiometric gain, overcoming kinetic limitations, solving thermodynamic barriers, circumventing toxic intermediates, uncoupling product synthesis from biomass formation, and altering redox cofactor specificity. The metabolic costs associated with bypass-implementation are likewise discussed, including tailoring their design towards improving bioproduction.

Intracellular biosensor-based dynamic regulation to manipulate gene expression at the spatiotemporal level

The use of intracellular, biosensor-based dynamic regulation strategies to regulate and improve the production of useful compounds have progressed significantly over previous decades. By employing such an approach, it is possible to simultaneously realize high productivity and optimum growth states. However, industrial fermentation conditions contain a mixture of high- and low-performance non-genetic variants, as well as young and aged cells at all growth phases. Such significant individual variations would hinder the precise controlling of metabolic flux at the single-cell level to achieve high productivity at the macroscopic population level. Intracellular biosensors, as the regulatory centers of metabolic networks, can real-time sense intra- and extracellular conditions and, thus, could be synthetically adapted to balance the biomass formation and overproduction of compounds by individual cells. Herein, we highlight advances in the designing and engineering approaches to intracellular biosensors. Then, the spatiotemporal properties of biosensors associated with the distribution of inducers are compared. Also discussed is the use of such biosensors to dynamically control the cellular metabolic flux. Such biosensors could achieve single-cell regulation or collective regulation goals, depending on whether or not the inducer distribution is only intracellular.

Rational engineering in Escherichia coli for high-titer production of baicalein based on genome-scale target identification

Baicalein is a bioactive flavonoid isolated from the traditional Chinese medicinal plant, Scutellaria baicalensis Georgi. Microbial synthesis of flavonoids has been intensively developed owing to the eco-friendly nature of the process. However, the titer of the flavonoids obtained is still at a low level, and effective methods to enhance these titers are lacking. In this study, the synthetic performance of baicalein-producing engineered E. coli was rationally evaluated to enhanced the expression of key enzymes. Transcriptional analyses of baicalein-overproducing strain and a control strain enabled the identification of 13 beneficial genes, including 8 genes that are seemingly irrelevant to baicalein metabolism. With the combination of the enzyme assembly and modularization strategy, the engineered DN-8 strain produced 367.8 mg/L baicalein in fed-batch fermentation, the maximum titer reported to date. This article is protected by copyright. All rights reserved.

Synthetic metabolism for biohalogenation

The pressing need for novel bioproduction approaches faces a limitation in the number and type of molecules accessed through synthetic biology. Halogenation is widely used for tuning physicochemical properties of molecules and polymers, but traditional halogenation chemistry often lacks specificity and generates harmful by-products. Here, we pose that deploying synthetic metabolism tailored for biohalogenation represents an unique opportunity towards economically attractive and environmentally friendly organohalide production. On this background, we discuss growth-coupled selection of functional metabolic modules that harness the rich repertoire of biosynthetic and biodegradation capabilities of environmental bacteria for in vivo biohalogenation. By rationally combining these approaches, the chemical landscape of living cells can accommodate bioproduction of added-value organohalides which, as of today, are obtained by traditional chemistry.

Genome-scale target identification in Escherichia coli for high-titer production of free fatty acids

To construct a superior microbial cell factory for chemical synthesis, a major challenge is to fully exploit cellular potential by identifying and engineering beneficial gene targets in sophisticated metabolic networks. Here, we take advantage of CRISPR interference (CRISPRi) and omics analyses to systematically identify beneficial genes that can be engineered to promote free fatty acids (FFAs) production in Escherichia coli. CRISPRi-mediated genetic perturbation enables the identification of 30 beneficial genes from 108 targets related to FFA metabolism. Then, omics analyses of the FFAs-overproducing strains and a control strain enable the identification of another 26 beneficial genes that are seemingly irrelevant to FFA metabolism. Combinatorial perturbation of four beneficial genes involving cellular stress responses results in a recombinant strain ihfA^L−-aidB⁺-ryfA^M−-gadA^H−, producing 30.0 g L⁻¹ FFAs in fed-batch fermentation, the maximum titer in E. coli reported to date. Our findings are of help in rewiring cellular metabolism and interwoven intracellular processes to facilitate high-titer production of biochemicals.

Identification of gene targets is one of the major challenges to construct superior microbial cell factory for chemical synthesis. Here, the authors employ CRISPRi and omics analyses for genome-scale target genes identification for high-titer production of free fatty acids in E. coli.

Anodic electro-fermentation: Empowering anaerobic production processes via anodic respiration

In nature as well as in industrial microbiology, all microorganisms need to achieve redox balance. Their redox state and energy conservation highly depend on the availability of a terminal electron acceptor, for example oxygen in aerobic production processes. Under anaerobic conditions in the absence of an electron acceptor, redox balance is achieved via the production of reduced carbon-compounds (fermentation). An alternative strategy to artificially stabilize microbial redox and energy state is the use of anodic electro-fermentation (AEF). This emerging biotechnology empowers respiration under anaerobic conditions using the anode of a bioelectrochemical system as an undepletable terminal electron acceptor. Electrochemical control of redox metabolism and energy conservation via AEF can steer the carbon metabolism towards a product of interest and avoid the need for continuous and cost-inefficient supply of oxygen as well as the production of mixed reduced by-products, as is the case in aerobic production and fermentation processes, respectively. The great challenge for AEF is to establish efficient extracellular electron transfer (EET) from the microbe to the anode and link it to central carbon metabolism to enhance the synthesis of a target product. This article reviews the advantages and challenges of AEF, EET mechanisms, microbial energy gain, and discusses the rational choice of substrate-product couple as well as the choice of microbial catalyst. Besides, it discusses the potential of the industrial model-organism Bacillus subtilis as a promising candidate for AEF, which has not been yet considered for such an application. This prospective review contributes to a better understanding of how industrial microbiology can benefit from AEF and analyses key-factors required to successfully implement AEF processes. Overall, this work aims to advance the young research field especially by critically revisiting the fundamental aspects of AEF.

Poly(3-hydroxypropionate): Biosynthesis Pathways and Malonyl-CoA Biosensor Material Properties

Many single-use non-degradable plastics are a threat to life today, and several polyhydroxyalkanoates (PHAs) biopolymers have been developed in the bioplastic industry to place petrochemical-based plastics. One of such is the novel biomaterial poly(3-hydroxypropionate) [poly(3HP)] because of its biocompatibility, biodegradability, and high yield synthesis using engineered strains. To date, many bio-polymer-based functional composites have been developed to increase the value of raw microbial-biopolymers obtained from cheap sources. This review article broadly covers poly(3HP), a comprehensive summary of critical biosynthetic production pathways comparing the yields and titers achieved in different Microbial cell Factories. This article also provides extensive knowledge and highlights recent progress on biosensors' use to optimize poly(3HP) production, some bacteria host adopted for production, chemical and physical properties, life cycle assessment for poly(3HP) production using corn oil as carbon source, and some essential medical applications of poly(3HP).

Does co-expression of Yarrowia lipolytica genes encoding Yas1p, Yas2p and Yas3p make a potential alkane-responsive biosensor in Saccharomyces cerevisiae?

Alkane-based biofuels are desirable to produce at a commercial scale as these have properties similar to current petroleum-derived transportation fuels. Rationally engineering microorganisms to produce a desirable compound, such as alkanes, is, however, challenging. Metabolic engineers are therefore increasingly implementing evolutionary engineering approaches combined with high-throughput screening tools, including metabolite biosensors, to identify productive cells. Engineering Saccharomyces cerevisiae to produce alkanes could be facilitated by using an alkane-responsive biosensor, which can potentially be developed from the native alkane-sensing system in Yarrowia lipolytica, a well-known alkane-assimilating yeast. This putative alkane-sensing system is, at least, based on three different transcription factors (TFs) named Yas1p, Yas2p and Yas3p. Although this system is not fully elucidated in Y. lipolytica, we were interested in evaluating the possibility of translating this system into an alkane-responsive biosensor in S. cerevisiae. We evaluated the alkane-sensing system in S. cerevisiae by developing one sensor based on the native Y. lipolytica ALK1 promoter and one sensor based on the native S. cerevisiae CYC1 promoter. In both systems, we found that the TFs Yas1p, Yas2p and Yas3p do not seem to act in the same way as these have been reported to do in their native host. Additional analysis of the TFs suggests that more knowledge regarding their mechanism is needed before a potential alkane-responsive sensor based on the Y. lipolytica system can be established in S. cerevisiae.

Homology-dependent recombination of large synthetic pathways into E. coli genome via λ-Red and CRISPR/Cas9 dependent selection methodology

Background

Metabolic engineering frequently needs genomic integration of many heterologous genes for biosynthetic pathway assembly. Despite great progresses in genome editing for the model microorganism Escherichia coli, the integration of large pathway into genome for stabilized chemical production is still challenging compared with small DNA integration.

Results

We have developed a λ-Red assisted homology-dependent recombination for large synthetic pathway integration in E. coli. With this approach, we can integrate as large as 12 kb DNA module into the chromosome of E. coli W3110 in a single step. The efficiency of this method can reach 100%, thus markedly improve the integration efficiency and overcome the limitation of the integration size adopted the common method. Furthermore, the limiting step in the methylerythritol 4-phosphate (MEP) pathway and lycopene synthetic pathway were integrated into the W3110 genome using our system. Subsequently, the yields of the final strain were increased 106 and 4.4-fold compared to the initial strain and the reference strain, respectively.

Conclusions

In addition to pre-existing method, our system presents an optional strategy for avoiding using plasmids and a valuable tool for large synthetic pathway assembly in E. coli.

Engineering a growth-phase-dependent biosynthetic pathway for carotenoid production in Saccharomyces cerevisiae

Metabolic engineering is usually focused on static control of microbial cell factories to efficient production of interested chemicals, though heterologous pathways compete with endogenous metabolism. However, products like carotenoids may cause metabolic burden on engineering strains, thus limiting product yields and influencing strain growth. Herein, a growth-phase-dependent regulation was developed to settle this matter, and its efficiency was verified using the heterogenous biosynthesis of lycopene in Saccharomyces cerevisiae as an example. Through growth-phase-dependent control of the lycopene biosynthetic pathway, limited step in MVA pathway, and competitive squalene pathway, production yield was increased by approximately 973-fold (from 0.034- to 33.1-mg/g CDW) and 1.48 g/L of production was obtained by one-stage fermentation in a 5-L bioreactor. Our study not only introduces an economically approach to the production of carotenoids, but also provides an example of dynamic regulation of biosynthetic pathways for metabolic engineering.

Systems and synthetic biology tools for advanced bioproduction hosts

The genomic revolution ushered in an era of discovery and characterization of enzymes from novel organisms that fueled engineering of microbes to produce commodity and high-value compounds. Over the past decade advances in synthetic biology tools in recent years contributed to significant progress in metabolic engineering efforts to produce both biofuels and bioproducts resulting in several such related items being brought to market. These successes represent a burgeoning bio-economy; however, significant resources and time are still necessary to progress a system from proof-of-concept to market. In order to fully realize this potential, methods that examine biological systems in a comprehensive, systematic and high-throughput manner are essential. Recent success in synthetic biology has coincided with the development of systems biology and analytical approaches that kept pace and scaled with technology development. Here, we review a selection of systems biology methods and their use in synthetic biology approaches for microbial biotechnology platforms.

Enhancing control of cell-free metabolism through pH modulation

Engineering metabolism for the synthesis of bio-based products in non-model organisms can be challenging. One specific challenge is that biosynthetic pathways are often built from enzyme candidates sourced from diverse organisms, which can prove difficult to implement in recombinant hosts due to differences in their cellular environments (e.g. pH, cofactor balance). To address this problem, we report a cell-free synthetic biology approach for understanding metabolism in a range of environmental conditions, specifically under varied pH. The key idea is to control the pH of Escherichia coli-based cell-free systems for assessing pathway performance using enzymes sourced from organisms other than E. coli. As a model, we apply this approach to study the impact of pH on the n-butanol biosynthesis pathway derived from clostridia in E. coli lysates. Specifically, we exploit the open, cell-free reaction environment to explore pH outside the habitable range of E. coli, revealing insights into how chemical context impacts the interaction between native metabolism and heterologous enzymes. We find that the pH optimum for butanol production from acetyl-CoA is substantially lower than the optimal pH of glycolysis in E. coli-based crude lysates. In addition, pH is an essential factor to consider when activating metabolic pathways in the cell-free environment due to its effect on reaction yield or enzyme activity, the latter of which is demonstrated in this work for alcohol dehydrogenases from a range of extremophiles. Ultimately, altering metabolism through pH control will allow cell-free systems to be used in studying the metabolic state of organisms and identify suitable enzymes for pathway engineering.

Expanding the Dynamic Range of a Transcription Factor-Based Biosensor in Saccharomyces cerevisiae

Metabolite biosensors are useful tools for high-throughput screening approaches and pathway regulation approaches. An important feature of biosensors is the dynamic range. To expand the maximum dynamic range of a transcription factor-based biosensor in Saccharomyces cerevisiae, using the fapO/FapR system from Bacillus subtilis as an example case, five native promoters, including constitutive and glucose-regulated ones, were modified. By evaluating different binding site (BS) positions in the core promoters, we identified locations that resulted in a high maximum dynamic range with low expression under repressed conditions. We further identified BS positions in the upstream element region of the TEF1 promoter that did not influence the native promoter strength but resulted in repression in the presence of a chimeric repressor consisting of FapR and the yeast repressor Mig1. These modified promoters with broad dynamic ranges will provide useful information for the engineering of future biosensors and their use in complex genetic circuits.

FadR-Based Biosensor-Assisted Screening for Genes Enhancing Fatty Acyl-CoA Pools in Saccharomyces cerevisiae

Fatty acid-derived compounds have a range of industrial applications, from chemical building blocks to biofuels. Due to the highly dynamic nature of fatty acid metabolism, it is difficult to identify genes modulating fatty acyl-CoA levels using a rational approach. Metabolite biosensors can be used to screen genes from large-scale libraries in vivo in a high throughput manner. Here, a fatty acyl-CoA sensor based on the transcription factor FadR from Escherichia coli was established in Saccharomyces cerevisiae and combined with a gene overexpression library to screen for genes increasing the fatty acyl-CoA pool. Fluorescence-activated cell sorting, followed by data analysis, identified genes enhancing acyl-CoA levels. From these, overexpression of RTC3, GGA2, and LPP1 resulted in about 80% increased fatty alcohol levels. Changes in fatty acid saturation and chain length distribution could also be observed. These results indicate that the use of this acyl-CoA biosensor combined with a gene overexpression library allows for identification of gene targets improving production of fatty acids and derived products.