Acceleration of target production in co-culture by enhancing intermediate consumption through adaptive laboratory evolution

A growth-coupling strategy for improving the stability of terpenoid bioproduction in Escherichia coli

BACKGROUND

Achieving cost-competitiveness remains challenging for industrial biomanufacturing. With whole-cell biocatalysis, inefficiency presents when individual cells vary in their production levels. The problem exacerbates when the basis for such production heterogeneity is heritable. Here, evolution selects for the low- and non-producers, as they have lowered/abolished the cost of bioproduction to fitness. With the scale of population expansion required for industrial bioproduction, the asymmetrical enrichment can be severe enough to compromise the performance, and hence commercial viability of the bioprocess. Clearly, addressing production heterogeneity is crucial, especially in improving the stability of bioproduction across the cell generations. In this respect, we designed a growth-coupling strategy for terpenoid bioproduction in Escherichia coli. By knocking out the native 1-deoxy-D-xylulose 5-phosphate reductoisomerase (dxr) gene and introducing the heterologous mevalonate pathway, we created a chassis that relies solely on the latter for synthesis of all terpenoids. We hypothesise that the need to sustain the biosynthesis of endogenous life-sustaining terpenoids will impose a minimum level of productivity, which concomitantly improves the bioproduction of our target terpenoid.

RESULTS

Following the confirmation of lethality of a dxr knockout, we challenged the strains with a continuous plasmid-based bioproduction of linalool. The Δdxr strain achieved an improved productivity profile in the first three days post-inoculation when compared to the parental strain. Productivity of the Δdxr strain remained observable near the end of 12 days, and after a disruption in nutrient and oxygen supply in a separate run. Unlike the parental strain, the Δdxr strain did not evolve the same deleterious mutations in the mevalonate pathway, nor a viable subgroup that had lost its resistance to the antibiotic selection pressure (a plausible plasmid loss event). We believe that this divergence in the evolution trajectories is indicative of a successful growth-coupling.

CONCLUSION

We have demonstrated a proof of concept of a growth-coupling strategy that improves the performance, and stability of terpenoid bioproduction across cell generations. The strategy is relatively broad in scope, and easy to implement in the background as a 'fail-safe' against a fall in productivity below the imposed minimum. We thus believe this work will find widespread utility in our collective effort towards industrial bioproduction.

Coupling and uncoupling growth and product formation for producing chemicals

Microbial fermentation employs two strategies: growth- and nongrowth-coupled productions. Stoichiometric metabolic models with flux balance analysis enable pathway engineering to couple target synthesis with growth, yielding numerous successful results. Growth-coupled engineering also contributes to improving bottleneck flux through subsequent adaptive evolution. However, because growth-coupled production inevitably shares resources between biomass and target syntheses, the cost-effective production of bulk chemicals mandates a nongrowth-coupled approach. In such processes, understanding how and when to transition the metabolic state from growth to production modes becomes crucial, as does maintaining cellular activity during the nongrowing state to achieve high productivity. In this paper, we review recent technologies for growth-coupled and nongrowth-coupled production, considering their advantages and disadvantages.

Co-Cultivated Enzyme Constraint Metabolic Network Model for Rational Guidance in Constructing Synthetic Consortia to Achieve Optimal Pathway Allocation Prediction

Synthetic consortia have emerged as a promising biosynthetic platform that offers new opportunities for biosynthesis. Genome-scale metabolic network models (GEMs) with complex constraints are extensively utilized to guide the synthesis in monocultures. However, few methods are currently available to guide the rational construction of synthetic consortia for predicting the optimal allocation strategy of synthetic pathways aimed at enhancing product synthesis. A standardized method to construct the co-cultivated Enzyme Constraint metabolic network model (CulECpy) is proposed, which integrates enzyme constraints and modular interaction scale constraints based on the research concept of "independent + global". This method is applied to construct several synthetic consortia models, which encompassed different target products, strains, synthetic pathways, and compositional structures. Analyzing the model, the optimal pathway allocation and initial inoculum ratio that enhance the synthesis of target products by synthetic consortia are predicted and verified. When comparing with the constructed co-culture synthesis system, the normalized root mean square error of all optimal theoretical yield simulations is found to be less than or equal to 0.25. The analyses and verifications demonstrate that the method CulECpy can guide the rational construction of synthetic consortia systems to facilitate biochemical synthesis.

Top-down and bottom-up microbiome engineering approaches to enable biomanufacturing from waste biomass

Growing environmental concerns and the need to adopt a circular economy have highlighted the importance of waste valorization for resource recovery. Microbial consortia-enabled biotechnologies have made significant developments in the biomanufacturing of valuable resources from waste biomass that serve as suitable alternatives to petrochemical-derived products. These microbial consortia-based processes are designed following a top-down or bottom-up engineering approach. The top-down approach is a classical method that uses environmental variables to selectively steer an existing microbial consortium to achieve a target function. While high-throughput sequencing has enabled microbial community characterization, the major challenge is to disentangle complex microbial interactions and manipulate the structure and function accordingly. The bottom-up approach uses prior knowledge of the metabolic pathway and possible interactions among consortium partners to design and engineer synthetic microbial consortia. This strategy offers some control over the composition and function of the consortium for targeted bioprocesses, but challenges remain in optimal assembly methods and long-term stability. In this review, we present the recent advancements, challenges, and opportunities for further improvement using top-down and bottom-up approaches for microbiome engineering. As the bottom-up approach is relatively a new concept for waste valorization, this review explores the assembly and design of synthetic microbial consortia, ecological engineering principles to optimize microbial consortia, and metabolic engineering approaches for efficient conversion. Integration of top-down and bottom-up approaches along with developments in metabolic modeling to predict and optimize consortia function are also highlighted.

ONE-SENTENCE SUMMARY

This review highlights the microbial consortia-driven waste valorization for biomanufacturing through top-down and bottom-up design approaches and describes strategies, tools, and unexplored opportunities to optimize the design and stability of such consortia.

Adaptive Laboratory Evolution of Microorganisms: Methodology and Application for Bioproduction

Adaptive laboratory evolution (ALE) is a useful experimental methodology for fundamental scientific research and industrial applications to create microbial cell factories. By using ALE, cells are adapted to the environment that researchers set based on their objectives through the serial transfer of cell populations in batch cultivations or continuous cultures and the fitness of the cells (i.e., cell growth) under such an environment increases. Then, omics analyses of the evolved mutants, including genome sequencing, transcriptome, proteome and metabolome analyses, are performed. It is expected that researchers can understand the evolutionary adaptation processes, and for industrial applications, researchers can create useful microorganisms that exhibit increased carbon source availability, stress tolerance, and production of target compounds based on omics analysis data. In this review article, the methodologies for ALE in microorganisms are introduced. Moreover, the application of ALE for the creation of useful microorganisms as cell factories has also been introduced.

Conversion of Mevalonate to Isoprenol Using Light Energy in Escherichia coli without Consuming Sugars for ATP Supply

Bioconversion of key intermediate metabolites such as mevalonate into various useful chemicals is a promising strategy for microbial production. However, the conversion of mevalonate into isoprenoids requires a supply of adenosine triphosphate (ATP). Light-driven ATP regeneration using microbial rhodopsin is an attractive module for improving the intracellular ATP supply. In the present study, we demonstrated the ATP-consuming conversion of mevalonate to isoprenol using rhodopsin-expressing Escherichia coli cells as a whole-cell catalyst in a medium that does not contain energy cosubstrate, such as glucose. Heterologous genes for the synthesis of isoprenol from mevalonate, which requires three ATP molecules for the series of reactions, and a delta-rhodopsin gene derived from Haloterrigena turkmenica were cointroduced into E. coli. To evaluate the conversion efficiency of mevalonate to isoprenol, the cells were suspended in a synthetic medium containing mevalonate as the sole carbon source and incubated under dark or light illumination (100 μmol m^-2 s^-1). The specific isoprenol production rates were 10.0 ± 0.9 and 20.4 ± 0.7 μmol gDCW^-1 h^-1 for dark and light conditions, respectively. The conversion was successfully enhanced under the light condition. Furthermore, the conversion efficiency increased with increasing illumination intensity, suggesting that ATP regenerated by the proton motive force generated by rhodopsin using light energy can drive ATP-consuming reactions in the whole-cell catalyst.

Metabolic pathway design for growth-associated phenylalanine production using synthetically designed mutualism

Combination of growth-associated pathway engineering based on flux balance analysis (FBA) and adaptive laboratory evolution (ALE) is a powerful approach to enhance the production of useful compounds. However, the feasibility of such growth-associated pathway designs depends on the type of target compound. In the present study, FBA predicted a set of gene deletions (pykA, pykF, ppc, zwf, and adhE) that leads to growth-associated phenylalanine production in Escherichia coli. The knockout strain is theoretically enforced to produce phenylalanine only at high growth yields, and could not be applied to the ALE experiment because of a severe growth defect. To overcome this challenge, we propose a novel approach for ALE based on mutualistic co-culture for coupling growth and production, regardless of the growth rate. We designed a synthetic mutualism of a phenylalanine-producing leucine-auxotrophic strain (KF strain) and a leucine-producing phenylalanine-auxotrophic strain (KL strain) and performed an ALE experiment for approximately 160 generations. The evolved KF strain (KF-E strain) grew in a synthetic medium (with glucose as the main carbon source) supplemented with leucine, while severe growth defects were observed in the parental KF strain. The phenylalanine yield of the KF-E strain was 2.3 times higher than that of the KF strain.