Miniaturized and automated adaptive laboratory evolution: Evolving Corynebacterium glutamicum towards an improved d-xylose utilization

Improving salt-tolerant artificial consortium of Bacillus amyloliquefaciens for bioconverting food waste to lipopeptides

High-salt content in food waste (FW) affects its resource utilization during biotransformation. In this study, adaptive laboratory evolution (ALE), gene editing, and artificial consortia were performed out to improve the salt-tolerance of Bacillus amyloliquefaciens for producing lipopeptide under FW and seawater. High-salt stress significantly decreased lipopeptide production in the B. amyloliquefaciens HM618 and ALE strains. The total lipopeptide production in the recombinant B. amyloliquefaciens HM-4KSMSO after overexpressing the ion transportor gene ktrA and proline transporter gene opuE and replacing the promoter of gene mrp was 1.34 times higher than that in the strain HM618 in medium containing 30 g/L NaCl. Lipopeptide production under salt-tolerant consortia containing two strains (HM-4KSMSO and Corynebacterium glutamicum) and three-strains (HM-4KSMSO, salt-tolerant C. glutamicum, and Yarrowia lipolytica) was 1.81- and 2.28-fold higher than that under pure culture in a medium containing FW or both FW and seawater, respectively. These findings provide a new strategy for using high-salt FW and seawater to produce value-added chemicals.

Itaconate Production from Crude Substrates with U. maydis: Scale-up of an Industrially Relevant Bioprocess

BACKGROUND

Industrial by-products accrue in most agricultural or food-related production processes, but additional value chains have already been established for many of them. Crude glycerol has a 60% lower market value than commercial glucose, as large quantities are produced in the biodiesel industry, but its valorisation is still underutilized. Due to its high carbon content and the natural ability of many microorganisms to metabolise it, microbial upcycling is a suitable option for this waste product.

RESULTS

In this work, the use of crude glycerol for the production of the value-added compound itaconate is demonstrated using the smut fungus Ustilago maydis. Starting with a highly engineered strain, itaconate production from an industrial glycerol waste stream was quickly established on a small scale, and the resulting yields were already competitive with processes using commercial sugars. Adaptive laboratory evolution resulted in an evolved strain with a 72% increased growth rate on glycerol. In the subsequent development and optimisation of a fed-batch process on a 1.5-2 L scale, the use of molasses, a side stream of sugar beet processing, eliminated the need for other expensive media components such as nitrogen or vitamins for biomass growth. The optimised process was scaled up to 150 L, achieving an overall titre of 72 g L- 1, a yield of 0.34 g g- 1, and a productivity of 0.54 g L- 1 h- 1.

CONCLUSIONS

Pilot-scale itaconate production from the complementary waste streams molasses and glycerol has been successfully established. In addition to achieving competitive performance indicators, the proposed dual feedstock strategy offers lower process costs and carbon footprint for the production of bio-based itaconate.

Engineering Escherichia coli for Isobutanol Production from Xylose or Glucose-Xylose Mixture

Aiming to overcome the depletion of fossil fuels and serious environmental pollution, biofuels such as isobutanol have garnered increased attention. Among different synthesis methods, the microbial fermentation of isobutanol from raw substrate is a promising strategy due to its low cost and environmentally friendly and optically pure products. As an important component of lignocellulosics and the second most common sugar in nature, xylose has become a promising renewable resource for microbial production. However, bottlenecks in xylose utilization limit its wide application as substrates. In this work, an isobutanol synthetic pathway from xylose was first constructed in E. coli MG1655 through the combination of the Ehrlich and Dahms pathways. The engineering of xylose transport and electron transport chain complexes further improved xylose assimilation and isobutanol production. By optimizing xylose supplement concentration, the recombinant E. coli strain BWL4 could produce 485.35 mg/L isobutanol from 20 g/L of xylose. To our knowledge, this is the first report related to isobutanol production using xylose as a sole carbon source in E. coli. Additionally, a glucose-xylose mixture was utilized as the carbon source. The Entner-Doudorof pathway was used to assimilate glucose, and the Ehrlich pathway was applied for isobutanol production. After carefully engineering the recombinant E. coli, strain BWL9 could produce 528.72 mg/L isobutanol from a mixture of 20 g/L glucose and 10 g/L xylose. The engineering strategies applied in this work provide a useful reference for the microbial production of isobutanol from xylose or glucose-xylose mixture.

Development of a 2-hydroxyglutarate production system by Corynebacterium glutamicum

2-Oxoglutarate (2-OG) is a tricarboxylate cycle intermediate that can be biologically converted into several industrially important compounds. However, studies on the fermentative production of compounds synthesized from 2-OG, but not via glutamate (defined as 2-OG derivatives), have been limited. Herein, a system that can efficiently produce 2-hydroxyglutarate (2-HG), a 2-OG derivative biosynthesized by the hgdH-encoded NADH-dependent 2-HG dehydrogenase of Acidaminococcus fermentans, was developed as a model using Corynebacterium glutamicum. First, the D3 strain, which lacked the two NADH-consuming enzymes, lactate dehydrogenase and malate dehydrogenase, as well as isocitrate lyase, was constructed as a starting strain. Next, the growth conditions that induced the accumulation of 2-OG were investigated, and it was found that the biotin- and nitrogen-limited (B/N-limited) aerobic growth conditions were suitable for this purpose. Finally, the hgdH gene of A. fermentans became overexpressed in the D3 strain by inserting it into the intergenic regions with the strong constitutive promoter of the tuf gene of C. glutamicum; the engineered strain was cultured under the B/N-limited aerobic growth conditions. The engineered strain produced 80.1 mM 2-HG with a yield of 0.390 mol/mol glucose, which are the highest titer and yield reported thus far, to the best of our knowledge. Furthermore, reverse genetics showed that the produced 2-HG was partially exported via the YggB protein (NCgl1221 protein, a mechanosensitive channel) known as an exporter for glutamate under the conditions used herein. KEY POINTS: • An efficient 2-HG production system was developed with Corynebacterium glutamicum. • Biotin- and nitrogen-limited aerobic growth conditions induced 2-OG production. • Produced 2-HG was partially excreted via the glutamate exporter, YggB.

From Saccharomyces cerevisiae to Ethanol: Unlocking the Power of Evolutionary Engineering in Metabolic Engineering Applications

Increased human population and the rapid decline of fossil fuels resulted in a global tendency to look for alternative fuel sources. Environmental concerns about fossil fuel combustion led to a sharp move towards renewable and environmentally friendly biofuels. Ethanol has been the primary fossil fuel alternative due to its low carbon emission rates, high octane content and comparatively facile microbial production processes. In parallel to the increased use of bioethanol in various fields such as transportation, heating and power generation, improvements in ethanol production processes turned out to be a global hot topic. Ethanol is by far the leading yeast output amongst a broad spectrum of bio-based industries. Thus, as a well-known platform microorganism and native ethanol producer, baker's yeast Saccharomyces cerevisiae has been the primary subject of interest for both academic and industrial perspectives in terms of enhanced ethanol production processes. Metabolic engineering strategies have been primarily adopted for direct manipulation of genes of interest responsible in mainstreams of ethanol metabolism. To overcome limitations of rational metabolic engineering, an alternative bottom-up strategy called inverse metabolic engineering has been widely used. In this context, evolutionary engineering, also known as adaptive laboratory evolution (ALE), which is based on random mutagenesis and systematic selection, is a powerful strategy to improve bioethanol production of S. cerevisiae. In this review, we focus on key examples of metabolic and evolutionary engineering for improved first- and second-generation S. cerevisiae bioethanol production processes. We delve into the current state of the field and show that metabolic and evolutionary engineering strategies are intertwined and many metabolically engineered strains for bioethanol production can be further improved by powerful evolutionary engineering strategies. We also discuss potential future directions that involve recent advancements in directed genome evolution, including CRISPR-Cas9 technology.

Robotic workflows for automated long-term adaptive laboratory evolution: improving ethanol utilization by Corynebacterium glutamicum

BACKGROUND

Adaptive laboratory evolution (ALE) is known as a powerful tool for untargeted engineering of microbial strains and genomics research. It is particularly well suited for the adaptation of microorganisms to new environmental conditions, such as alternative substrate sources. Since the probability of generating beneficial mutations increases with the frequency of DNA replication, ALE experiments are ideally free of constraints on the required duration of cell proliferation.

RESULTS

Here, we present an extended robotic workflow for performing long-term evolution experiments based on fully automated repetitive batch cultures (rbALE) in a well-controlled microbioreactor environment. Using a microtiter plate recycling approach, the number of batches and thus cell generations is technically unlimited. By applying the validated workflow in three parallel rbALE runs, ethanol utilization by Corynebacterium glutamicum ATCC 13032 (WT) was significantly improved. The evolved mutant strain WT_EtOH-Evo showed a specific ethanol uptake rate of 8.45 ± 0.12 mmolEtOH gCDW-1 h-1 and a growth rate of 0.15 ± 0.01 h-1 in lab-scale bioreactors. Genome sequencing of this strain revealed a striking single nucleotide variation (SNV) upstream of the ald gene (NCgl2698, cg3096) encoding acetaldehyde dehydrogenase (ALDH). The mutated basepair was previously predicted to be part of the binding site for the global transcriptional regulator GlxR, and re-engineering demonstrated that the identified SNV is key for enhanced ethanol assimilation. Decreased binding of GlxR leads to increased synthesis of the rate-limiting enzyme ALDH, which was confirmed by proteomics measurements.

CONCLUSIONS

The established rbALE technology is generally applicable to any microbial strain and selection pressure that fits the small-scale cultivation format. In addition, our specific results will enable improved production processes with C. glutamicum from ethanol, which is of particular interest for acetyl-CoA-derived products.

Metabolic engineering of Corynebacterium glutamicum for fatty alcohol production from glucose and wheat straw hydrolysate

BACKGROUND

Fatty acid-derived products such as fatty alcohols (FAL) find growing application in cosmetic products, lubricants, or biofuels. So far, FAL are primarily produced petrochemically or through chemical conversion of bio-based feedstock. Besides the well-known negative environmental impact of using fossil resources, utilization of bio-based first-generation feedstock such as palm oil is known to contribute to the loss of habitat and biodiversity. Thus, the microbial production of industrially relevant chemicals such as FAL from second-generation feedstock is desirable.

RESULTS

To engineer Corynebacterium glutamicum for FAL production, we deregulated fatty acid biosynthesis by deleting the transcriptional regulator gene fasR, overexpressing a fatty acyl-CoA reductase (FAR) gene of Marinobacter hydrocarbonoclasticus VT8 and attenuating the native thioesterase expression by exchange of the ATG to a weaker TTG start codon. C. glutamicum ∆fasR cg2692_TTG (pEKEx2-maqu2220) produced in shaking flasks 0.54 ± 0.02 g_FAL L^-1 from 20 g glucose L^-1 with a product yield of 0.054 ± 0.001 Cmol Cmol^-1. To enable xylose utilization, we integrated xylA encoding the xylose isomerase from Xanthomonas campestris and xylB encoding the native xylulose kinase into the locus of actA. This approach enabled growth on xylose. However, adaptive laboratory evolution (ALE) was required to improve the growth rate threefold to 0.11 ± 0.00 h^-1. The genome of the evolved strain C. glutamicum gX was re-sequenced, and the evolved genetic module was introduced into C. glutamicum ∆fasR cg2692_TTG (pEKEx2-maqu2220) which allowed efficient growth and FAL production on wheat straw hydrolysate. FAL biosynthesis was further optimized by overexpression of the pntAB genes encoding the membrane-bound transhydrogenase of E. coli. The best-performing strain C. glutamicum ∆fasR cg2692_TTG CgLP12::(P_tac-pntAB-T_rrnB) gX (pEKEx2-maqu2220) produced 2.45 ± 0.09 g_FAL L^-1 with a product yield of 0.054 ± 0.005 Cmol Cmol^-1 and a volumetric productivity of 0.109 ± 0.005 g_FAL L^-1 h^-1 in a pulsed fed-batch cultivation using wheat straw hydrolysate.

CONCLUSION

The combination of targeted metabolic engineering and ALE enabled efficient FAL production in C. glutamicum from wheat straw hydrolysate for the first time. Therefore, this study provides useful metabolic engineering principles to tailor this bacterium for other products from this second-generation feedstock.

From frozen cell bank to product assay: high-throughput strain characterisation for autonomous Design-Build-Test-Learn cycles

BACKGROUND

Modern genome editing enables rapid construction of genetic variants, which are further developed in Design-Build-Test-Learn cycles. To operate such cycles in high throughput, fully automated screening, including cultivation and analytics, is crucial in the Test phase. Here, we present the required steps to meet these demands, resulting in an automated microbioreactor platform that facilitates autonomous phenotyping from cryo culture to product assay.

RESULTS

First, an automated deep freezer was integrated into the robotic platform to provide working cell banks at all times. A mobile cart allows flexible docking of the freezer to multiple platforms. Next, precultures were integrated within the microtiter plate for cultivation, resulting in highly reproducible main cultures as demonstrated for Corynebacterium glutamicum. To avoid manual exchange of microtiter plates after cultivation, two clean-in-place strategies were established and validated, resulting in restored sterile conditions within two hours. Combined with the previous steps, these changes enable a flexible start of experiments and greatly increase the walk-away time.

CONCLUSIONS

Overall, this work demonstrates the capability of our microbioreactor platform to perform autonomous, consecutive cultivation and phenotyping experiments. As highlighted in a case study of cutinase-secreting strains of C. glutamicum, the new procedure allows for flexible experimentation without human interaction while maintaining high reproducibility in early-stage screening processes.

Microbial tolerance engineering for boosting lactic acid production from lignocellulose

Lignocellulosic biomass is an attractive non-food feedstock for lactic acid production via microbial conversion due to its abundance and low-price, which can alleviate the conflict with food supplies. However, a variety of inhibitors derived from the biomass pretreatment processes repress microbial growth, decrease feedstock conversion efficiency and increase lactic acid production costs. Microbial tolerance engineering strategies accelerate the conversion of carbohydrates by improving microbial tolerance to toxic inhibitors using pretreated lignocellulose hydrolysate as a feedstock. This review presents the recent significant progress in microbial tolerance engineering to develop robust microbial cell factories with inhibitor tolerance and their application for cellulosic lactic acid production. Moreover, microbial tolerance engineering crosslinking other efficient breeding tools and novel approaches are also deeply discussed, aiming to providing a practical guide for economically viable production of cellulosic lactic acid.

Application of Adaptive Laboratory Evolution in Lipid and Terpenoid Production in Yeast and Microalgae

Due to the complexity of metabolic and regulatory networks in microorganisms, it is difficult to obtain robust phenotypes through artificial rational design and genetic perturbation. Adaptive laboratory evolution (ALE) engineering plays an important role in the construction of stable microbial cell factories by simulating the natural evolution process and rapidly obtaining strains with stable traits through screening. This review summarizes the application of ALE technology in microbial breeding, describes the commonly used methods for ALE, and highlights the important applications of ALE technology in the production of lipids and terpenoids in yeast and microalgae. Overall, ALE technology provides a powerful tool for the construction of microbial cell factories, and it has been widely used in improving the level of target product synthesis, expanding the range of substrate utilization, and enhancing the tolerance of chassis cells. In addition, in order to improve the production of target compounds, ALE also employs environmental or nutritional stress strategies corresponding to the characteristics of different terpenoids, lipids, and strains.

Discovery of novel amino acid production traits by evolution of synthetic co-cultures

BACKGROUND

Amino acid production features of Corynebacterium glutamicum were extensively studied in the last two decades. Many metabolic pathways, regulatory and transport principles are known, but purely rational approaches often provide only limited progress in production optimization. We recently generated stable synthetic co-cultures, termed Communities of Niche-optimized Strains (CoNoS), that rely on cross-feeding of amino acids for growth. This setup has the potential to evolve strains with improved production by selection of faster growing communities.

RESULTS

Here we performed adaptive laboratory evolution (ALE) with a CoNoS to identify mutations that are relevant for amino acid production both in mono- and co-cultures. During ALE with the CoNoS composed of strains auxotrophic for either L-leucine or L-arginine, we obtained a 23% growth rate increase. Via whole-genome sequencing and reverse engineering, we identified several mutations involved in amino acid transport that are beneficial for CoNoS growth. The L-leucine auxotrophic strain carried an expression-promoting mutation in the promoter region of brnQ (cg2537), encoding a branched-chain amino acid transporter in combination with mutations in the genes for the Na⁺/H⁺-antiporter Mrp1 (cg0326-cg0321). This suggested an unexpected link of Mrp1 to L-leucine transport. The L-arginine auxotrophic partner evolved expression-promoting mutations near the transcriptional start site of the yet uncharacterized operon argTUV (cg1504-02). By mutation studies and ITC, we characterized ArgTUV as the only L-arginine uptake system of C. glutamicum with an affinity of K_D = 30 nM. Finally, deletion of argTUV in an L-arginine producer strain resulted in a faster and 24% higher L-arginine production in comparison to the parental strain.

CONCLUSION

Our work demonstrates the power of the CoNoS-approach for evolution-guided identification of non-obvious production traits, which can also advance amino acid production in monocultures. Further rounds of evolution with import-optimized strains can potentially reveal beneficial mutations also in metabolic pathway enzymes. The approach can easily be extended to all kinds of metabolite cross-feeding pairings of different organisms or different strains of the same organism, thereby enabling the identification of relevant transport systems and other favorable mutations.

Accelerated Adaptive Laboratory Evolution by Automated Repeated Batch Processes in Parallelized Bioreactors

Adaptive laboratory evolution (ALE) is a valuable complementary tool for modern strain development. Insights from ALE experiments enable the improvement of microbial cell factories regarding the growth rate and substrate utilization, among others. Most ALE experiments are conducted by serial passaging, a method that involves large amounts of repetitive manual labor and comes with inherent experimental design flaws. The acquisition of meaningful and reliable process data is a burdensome task and is often undervalued and neglected, but also unfeasible in shake flask experiments due to technical limitations. Some of these limitations are alleviated by emerging automated ALE methods on the μL and mL scale. A novel approach to conducting ALE experiments is described that is faster and more efficient than previously used methods. The conventional shake flask approach was translated to a parallelized, L scale stirred-tank bioreactor system that runs controlled, automated, repeated batch processes. The method was validated with a growth optimization experiment of E. coli K-12 MG1655 grown with glycerol minimal media as a benchmark. Off-gas analysis enables the continuous estimation of the biomass concentration and growth rate using a black-box model based on first principles (soft sensor). The proposed method led to the same stable growth rates of E. coli with the non-native carbon source glycerol 9.4 times faster than the traditional manual approach with serial passaging in uncontrolled shake flasks and 3.6 times faster than an automated approach on the mL scale. Furthermore, it is shown that the cumulative number of cell divisions (CCD) alone is not a suitable timescale for measuring and comparing evolutionary progress.

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.

Recent progress in adaptive laboratory evolution of industrial microorganisms

Adaptive laboratory evolution (ALE) is a technique for the selection of strains with better phenotypes by long-term culture under a specific selection pressure or growth environment. Because ALE does not require detailed knowledge of a variety of complex and interactive metabolic networks, and only needs to simulate natural environmental conditions in the laboratory to design a selection pressure, it has the advantages of broad adaptability, strong practicability, and more convenient transformation of strains. In addition, ALE provides a powerful method for studying the evolutionary forces that change the phenotype, performance, and stability of strains, resulting in more productive industrial strains with beneficial mutations. In recent years, ALE has been widely used in the activation of specific microbial metabolic pathways and phenotypic optimization, the efficient utilization of specific substrates, the optimization of tolerance to toxic substance, and the biosynthesis of target products, which is more conducive to the production of industrial strains with excellent phenotypic characteristics. In this paper, typical examples of ALE applications in the development of industrial strains and the research progress of this technology are reviewed, followed by a discussion of its development prospects.

Designer bacterial cell factories for improved production of commercially valuable non-ribosomal peptides

Non-ribosomal peptides have gained significant attention as secondary metabolites of high commercial importance. This group houses a diverse range of bioactive compounds, ranging from biosurfactants to antimicrobial and cytotoxic agents. However, low yield of synthesis by bacteria and excessive losses during purification hinders the industrial-scale production of non-ribosomal peptides, and subsequently limits their widespread applicability. While isolation of efficient producer strains and optimization of bioprocesses have been extensively used to enhance yield, further improvement can be made by optimization of the microbial strain using the tools and techniques of metabolic engineering, synthetic biology, systems biology, and adaptive laboratory evolution. These techniques, which directly target the genome of producer strains, aim to redirect carbon and nitrogen fluxes of the metabolic network towards the desired product, bypass the feedback inhibition and repression mechanisms that limit the maximum productivity of the strain, and even extend the substrate range of the cell for synthesis of the target product. The present review takes a comprehensive look into the biosynthesis of bacterial NRPs, how the same is regulated by the cell, and dives deep into the strategies that have been undertaken for enhancing the yield of NRPs, while also providing a perspective on other potential strategies that can allow for further yield improvement. Furthermore, this review provides the reader with a holistic perspective on the design of cellular factories of NRP production, starting from general techniques performed in the laboratory to the computational techniques that help a biochemical engineer model and subsequently strategize the architectural plan.

Recent Advances, Challenges and Metabolic Engineering Strategies in the Biosynthesis of 3-Hydroxypropionic Acid

As an attractive and valuable platform chemical, 3-hydroxypropionic acid (3-HP) can be used to produce a variety of industrially important commodity chemicals and biodegradable polymers. Moreover, the biosynthesis of 3-HP has drawn much attention in recent years due to its sustainability and environmental friendliness. Here, we focus on recent advances, challenges and metabolic engineering strategies in the biosynthesis of 3-HP. While glucose and glycerol are major carbon sources for its production of 3-HP via microbial fermentation, other carbon sources have also been explored. To increase yield and titer, synthetic biology and metabolic engineering strategies have been explored, including modifying pathway enzymes, eliminating flux blockages due to byproduct synthesis, eliminating toxic byproducts, and optimizing via genome-scale models. This review also provides insights on future directions for 3-HP biosynthesis. This article is protected by copyright. All rights reserved.

Communities of Niche-optimized Strains (CoNoS) - Design and creation of stable, genome-reduced co-cultures

Current bioprocesses for production of value-added compounds are mainly based on pure cultures that are composed of rationally engineered strains of model organisms with versatile metabolic capacities. However, in the comparably well-defined environment of a bioreactor, metabolic flexibility provided by various highly abundant biosynthetic enzymes is much less required and results in suboptimal use of carbon and energy sources for compound production. In nature, non-model organisms have frequently evolved in communities where genome-reduced, auxotrophic strains cross-feed each other, suggesting that there must be a significant advantage compared to growth without cooperation. To prove this, we started to create and study synthetic communities of niche-optimized strains (CoNoS) that consists of two strains of the same species Corynebacterium glutamicum that are mutually dependent on one amino acid. We used both the wild-type and the genome-reduced C1* chassis for introducing selected amino acid auxotrophies, each based on complete deletion of all required biosynthetic genes. The best candidate strains were used to establish several stably growing CoNoS that were further characterized and optimized by metabolic modelling, microfluidic experiments and rational metabolic engineering to improve amino acid production and exchange. Finally, the engineered CoNoS consisting of an l-leucine and l-arginine auxotroph showed a specific growth rate equivalent to 83% of the wild type in monoculture, making it the fastest co-culture of two auxotrophic C. glutamicum strains to date. Overall, our results are a first promising step towards establishing improved biobased production of value-added compounds using the CoNoS approach.

Sustainable production of astaxanthin in microorganisms: the past, present, and future

Astaxanthin (3,3'-dihydroxy-4,4'-diketo-β-carotene) is a type of C40 carotenoid with remarkable antioxidant characteristics, showing significant application prospects in many fields. Traditionally, the astaxanthin is mainly obtained from chemical synthesis and natural acquisition, with both approaches having many limitations and not capable of meeting the growing market demand. In order to cope with these challenges, novel techniques, e.g., the innovative cell engineering strategies, have been developed to increase the astaxanthin production. In this review, we first elaborated the biosynthetic pathway of astaxanthin, with the key enzymes and their functions discussed in the metabolic process. Then, we summarized the conventional, non-genetic strategies to promote the production of astaxanthin, including the methods of exogenous additives, mutagenesis, and adaptive evolution. Lastly, we reviewed comprehensively the latest studies on the synthesis of astaxanthin in various recombinant microorganisms based on the concept of microbial cell factory. Furthermore, we have proposed several novel technologies for improving the astaxanthin accumulation in several model species of microorganisms.

gcFront: a tool for determining a Pareto front of growth-coupled cell factory designs

Motivation

A widely applicable strategy to create cell factories is to knockout (KO) genes or reactions to redirect cell metabolism so that chemical synthesis is made obligatory when the cell grows at its maximum rate. Synthesis is thus growth-coupled, and the stronger the coupling the more deleterious any impediments in synthesis are to cell growth, making high producer phenotypes evolutionarily robust. Additionally, we desire that these strains grow and synthesize at high rates. Genome-scale metabolic models can be used to explore and identify KOs that growth-couple synthesis, but these are rare in an immense design space, making the search difficult and slow.

Results

To address this multi-objective optimization problem, we developed a software tool named gcFront—using a genetic algorithm it explores KOs that maximize cell growth, product synthesis and coupling strength. Moreover, our measure of coupling strength facilitates the search so that gcFront not only finds a growth-coupled design in minutes but also outputs many alternative Pareto optimal designs from a single run—granting users flexibility in selecting designs to take to the lab.

Availability and implementation

gcFront, with documentation and a workable tutorial, is freely available at GitHub: https://github.com/lLegon/gcFront and archived at Zenodo, DOI: 10.5281/zenodo.5557755.

Supplementary information

Supplementary data are available at Bioinformatics online.

Valorisation of xylose to renewable fuels and chemicals, an essential step in augmenting the commercial viability of lignocellulosic biorefineries

Biologists and engineers are making tremendous efforts in contributing to a sustainable and green society. To that end, there is growing interest in waste management and valorisation. Lignocellulosic biomass (LCB) is the most abundant material on the earth and an inevitable waste predominantly originating from agricultural residues, forest biomass and municipal solid waste streams. LCB serves as the renewable feedstock for clean and sustainable processes and products with low carbon emission. Cellulose and hemicellulose constitute the polymeric structure of LCB, which on depolymerisation liberates oligomeric or monomeric glucose and xylose, respectively. The preferential utilization of glucose and/or absence of the xylose metabolic pathway in microbial systems cause xylose valorization to be alienated and abandoned, a major bottleneck in the commercial viability of LCB-based biorefineries. Xylose is the second most abundant sugar in LCB, but a non-conventional industrial substrate unlike glucose. The current review seeks to summarize the recent developments in the biological conversion of xylose into a myriad of sustainable products and associated challenges. The review discusses the microbiology, genetics, and biochemistry of xylose metabolism with hurdles requiring debottlenecking for efficient xylose assimilation. It further describes the product formation by microbial cell factories which can assimilate xylose naturally and rewiring of metabolic networks to ameliorate xylose-based bioproduction in native as well as non-native strains. The review also includes a case study that provides an argument on a suitable pathway for optimal cell growth and succinic acid (SA) production from xylose through elementary flux mode analysis. Finally, a product portfolio from xylose bioconversion has been evaluated along with significant developments made through enzyme, metabolic and process engineering approaches, to maximize the product titers and yield, eventually empowering LCB-based biorefineries. Towards the end, the review is wrapped up with current challenges, concluding remarks, and prospects with an argument for intense future research into xylose-based biorefineries.

Synthetic Biology Toolkits and Metabolic Engineering Applied in Corynebacterium glutamicum for Biomanufacturing

Corynebacterium glutamicum is an important workhorse in industrial white biotechnology. It has been widely applied in the producing processes of amino acids, fuels, and diverse value-added chemicals. With the continuous disclosure of genetic regulation mechanisms, various strategies and technologies of synthetic biology were used to design and construct C. glutamicum cells for biomanufacturing and bioremediation. This study mainly aimed to summarize the design and construction strategies of C. glutamicum-engineered strains, which were based on genomic modification, synthetic biological device-assisted metabolic flux optimization, and directed evolution-based engineering. Then, taking two important bioproducts (N-acetylglucosamine and hyaluronic acid) as examples, the applications of C. glutamicum cell factories were introduced. Finally, we discussed the current challenges and future development trends of C. glutamicum-engineered strain construction.

Online estimation of changing metabolic capacities in continuous Corynebacterium glutamicum cultivations growing on a complex sugar mixture

Model‐based state estimators enable online monitoring of bioprocesses and, thereby, quantitative process understanding during running operations. During prolonged continuous bioprocesses strain physiology is affected by selection pressure. This can cause time‐variable metabolic capacities that lead to a considerable model‐plant mismatch reducing monitoring performance if model parameters are not adapted accordingly. Variability of metabolic capacities therefore needs to be integrated in the in silico representation of a process using model‐based monitoring approaches. To enable online monitoring of multiple concentrations as well as metabolic capacities during continuous bioprocessing of spent sulfite liquor with Corynebacterium glutamicum, this study presents a particle filtering framework that takes account of parametric variability. Physiological parameters are continuously adapted by Bayesian inference, using noninvasive off‐gas measurements. Additional information on current parameter importance is derived from time‐resolved sensitivity analysis. Experimental results show that the presented framework enables accurate online monitoring of long‐term culture dynamics, whereas state estimation without parameter adaption failed to quantify substrate metabolization and growth capacities under conditions of high selection pressure. Online estimated metabolic capacities are further deployed for multiobjective optimization to identify time‐variable optimal operating points. Thereby, the presented monitoring system forms a basis for adaptive control during continuous bioprocessing of lignocellulosic by‐product streams.

Biosensor-based growth-coupling and spatial separation as an evolution strategy to improve small molecule production of Corynebacterium glutamicum

Evolutionary engineering is a powerful method to improve the performance of microbial cell factories, but can typically not be applied to enhance the production of chemicals due to the lack of an appropriate selection regime. We report here on a new strategy based on transcription factor-based biosensors, which directly couple production to growth. The growth of Corynebacterium glutamicum was coupled to the intracellular concentration of branched-chain amino acids, by integrating a synthetic circuit based on the Lrp biosensor upstream of two growth-regulating genes, pfkA and hisD. Modelling and experimental data highlight spatial separation as key strategy to limit the selection of 'cheater' strains that escaped the evolutionary pressure. This approach facilitated the isolation of strains featuring specific causal mutations enhancing amino acid production. We envision that this strategy can be applied with the plethora of known biosensors in various microbes, unlocking evolution as a feasible strategy to improve production of chemicals.

Adaptive laboratory evolution principles and applications in industrial biotechnology

Adaptive laboratory evolution (ALE) is an innovative approach for the generation of evolved microbial strains with desired characteristics, by implementing the rules of natural selection as presented in the Darwinian Theory, on the laboratory bench. New as it might be, it has already been used by several researchers for the amelioration of a variety of characteristics of widely used microorganisms in biotechnology. ALE is used as a tool for the deeper understanding of the genetic and/or metabolic pathways of evolution. Another important field targeted by ALE is the manufacturing of products of (high) added value, such as ethanol, butanol and lipids. In the current review, we discuss the basic principles and techniques of ALE, and then we focus on studies where it has been applied to bacteria, fungi and microalgae, aiming to improve their performance to biotechnological procedures and/or inspect the genetic background of evolution. We conclude that ALE is a promising and efficacious method that has already led to the acquisition of useful new microbiological strains in biotechnology and could possibly offer even more interesting results in the future.

Understanding D-xylonic acid accumulation: a cornerstone for better metabolic engineering approaches

The xylose oxidative pathway (XOP) has been engineered in microorganisms for the production of a wide range of industrially relevant compounds. However, the performance of metabolically engineered XOP-utilizing microorganisms is typically hindered by D-xylonic acid accumulation. It acidifies the media and perturbs cell growth due to toxicity, thus curtailing enzymatic activity and target product formation. Fortunately, from the growing portfolio of genetic tools, several strategies that can be adapted for the generation of efficient microbial cell factories have been implemented to address D-xylonic acid accumulation. This review centers its discussion on the causes of D-xylonic acid accumulation and how to address it through different engineering and synthetic biology techniques with emphasis given on bacterial strains. In the first part of this review, the ability of certain microorganisms to produce and tolerate D-xylonic acid is also tackled as an important aspect in developing efficient microbial cell factories. Overall, this review could shed some insights and clarity to those working on XOP in bacteria and its engineering for the development of industrially applicable product-specialist strains. KEY POINTS: D-Xylonic acid accumulation is attributed to the overexpression of xylose dehydrogenase concomitant with basal or inefficient expression of enzymes involved in D-xylonic acid assimilation. Redox imbalance and insufficient cofactors contribute to D-xylonic acid accumulation. Overcoming D-xylonic acid accumulation can increase product formation among engineered strains. Engineering strategies involving enzyme engineering, evolutionary engineering, coutilization of different sugar substrates, and synergy of different pathways could potentially address D-xylonic acid accumulation.

(Optochemical) Control of Synthetic Microbial Coculture Interactions on a Microcolony Level

Synthetic microbial cocultures carry enormous potential for applied biotechnology and are increasingly the subject of fundamental research. So far, most cocultures have been designed and characterized based on bulk cultivations without considering the potentially highly heterogeneous and diverse single-cell behavior. However, an in-depth understanding of cocultures including their interacting single cells is indispensable for the development of novel cultivation approaches and control of cocultures. We present the development, validation, and experimental characterization of an optochemically controllable bacterial coculture on a microcolony level consisting of two Corynebacterium glutamicum strains. Our coculture combines an l-lysine auxotrophic strain together with a l-lysine-producing variant carrying the genetically IPTG-mediated induction of l-lysine production. We implemented two control approaches utilizing IPTG as inducer molecule. First, unmodified IPTG was supplemented to the culture enabling a medium-based control of the production of l-lysine, which serves as the main interacting component. Second, optochemical control was successfully performed by utilizing photocaged IPTG activated by appropriate illumination. Both control strategies were validated studying cellular growth on a microcolony level. The novel microfluidic single-cell cultivation strategies applied in this work can serve as a blueprint to validate cellular control strategies of synthetic mono- and cocultures with single-cell resolution at defined environmental conditions.

Microaerobic growth-decoupled production of α-ketoglutarate and succinate from xylose in a one-pot process using Corynebacterium glutamicum

BACKGROUND

Lignocellulosic biomass is the most abundant raw material on earth. Its efficient use for novel bio-based materials is essential for an emerging bioeconomy. Possible building blocks for such materials are the key TCA-cycle intermediates α-ketoglutarate and succinate. These organic acids have a wide range of potential applications, particularly in use as monomers for established or novel biopolymers. Recently, Corynebacterium glutamicum was successfully engineered and evolved towards an improved utilization of d-xylose via the Weimberg pathway, yielding the strain WMB2_evo . The Weimberg pathway enables a carbon-efficient C5-to-C5 conversion of d-xylose to α-ketoglutarate and a shortcut route to succinate as co-product in a one-pot process.

METHODS AND RESULTS

C. glutamicum WMB2_evo was grown under dynamic microaerobic conditions on d-xylose, leading to the formation of comparably high amounts of succinate and only small amounts of α-ketoglutarate. Subsequent carbon isotope labeling experiments verified the targeted production route for both products in C. glutamicum WMB2_evo . Fed-batch process development was initiated and the effect of oxygen supply and feeding strategy for a growth-decoupled co-production of α-ketoglutarate and succinate were studied in detail. The finally established fed-batch production process resulted in the formation of 78.4 mmol L^-1 (11.45 g L^-1 ) α-ketoglutarate and 96.2 mmol L^-1 (11.36 g L^-1 ) succinate.

CONCLUSION

The developed one-pot process represents a promising approach for the combined supply of bio-based α-ketoglutarate and succinate. Future work will focus on tailor-made down-stream processing of both organic acids from the fermentation broth to enable their application as building blocks in chemical syntheses. Alternatively, direct conversion of one or both acids via whole-cell or cell-free enzymatic approaches can be envisioned; thus, extending the network of value chains starting from cheap and renewable d-xylose.

Adaptive laboratory evolution accelerated glutarate production by Corynebacterium glutamicum

BACKGROUND

The demand for biobased polymers is increasing steadily worldwide. Microbial hosts for production of their monomeric precursors such as glutarate are developed. To meet the market demand, production hosts have to be improved constantly with respect to product titers and yields, but also shortening bioprocess duration is important.

RESULTS

In this study, adaptive laboratory evolution was used to improve a C. glutamicum strain engineered for production of the C5-dicarboxylic acid glutarate by flux enforcement. Deletion of the L-glutamic acid dehydrogenase gene gdh coupled growth to glutarate production since two transaminases in the glutarate pathway are crucial for nitrogen assimilation. The hypothesis that strains selected for faster glutarate-coupled growth by adaptive laboratory evolution show improved glutarate production was tested. A serial dilution growth experiment allowed isolating faster growing mutants with growth rates increasing from 0.10 h-1 by the parental strain to 0.17 h-1 by the fastest mutant. Indeed, the fastest growing mutant produced glutarate with a twofold higher volumetric productivity of 0.18 g L-1 h-1 than the parental strain. Genome sequencing of the evolved strain revealed candidate mutations for improved production. Reverse genetic engineering revealed that an amino acid exchange in the large subunit of L-glutamic acid-2-oxoglutarate aminotransferase was causal for accelerated glutarate production and its beneficial effect was dependent on flux enforcement due to deletion of gdh. Performance of the evolved mutant was stable at the 2 L bioreactor-scale operated in batch and fed-batch mode in a mineral salts medium and reached a titer of 22.7 g L-1, a yield of 0.23 g g-1 and a volumetric productivity of 0.35 g L-1 h-1. Reactive extraction of glutarate directly from the fermentation broth was optimized leading to yields of 58% and 99% in the reactive extraction and reactive re-extraction step, respectively. The fermentation medium was adapted according to the downstream processing results.

CONCLUSION

Flux enforcement to couple growth to operation of a product biosynthesis pathway provides a basis to select strains growing and producing faster by adaptive laboratory evolution. After identifying candidate mutations by genome sequencing causal mutations can be identified by reverse genetics. As exemplified here for glutarate production by C. glutamicum, this approach allowed deducing rational metabolic engineering strategies.

Programming adaptive laboratory evolution of 4-hydroxyisoleucine production driven by a lysine biosensor in Corynebacterium glutamicum

4-Hydroxyisoleucine (4-HIL) is a promising drug for treating diabetes. In our previous study, 4-HIL was synthesized from self-produced L-isoleucine (Ile) in Corynebacterium glutamicum by expressing an Ile dioxygenase gene. Although the 4-HIL production of recombinant strain SZ06 increased significantly, a by-product, L-lysine (Lys) was accumulated because of the share of the first several enzymes in Ile and Lys biosynthetic pathways. In this study, programming adaptive laboratory evolution (ALE) was designed and conducted in SZ06 to promote 4-HIL biosynthesis. At first, a programming evolutionary system pMK was constructed, which contains a Lys biosensor LysG-P_lysE and an evolutionary actuator composed of a mutagenesis gene and a fluorescent protein gene. The evolutionary strain SZ06/pMK was then let to be evolved programmatically and spontaneously by sensing Lys concentration. After successive rounds of evolution, nine mutant strains K1 - K9 with significantly increased 4-HIL production and growth performance were obtained. The maximum 4-HIL titer was 152.19 ± 14.60 mM, 28.4% higher than that in SZ06. This titer was higher than those of all the metabolic engineered C. glutamicum strains ever constructed. The whole genome sequencing of the nine evolved strains revealed approximately 30 genetic mutations in each strain. Only one mutation was directly related to the Lys biosynthetic pathway. Therefore, programming ALE driven by Lys biosensor can be used as an effective strategy to increase 4-HIL production in C. glutamicum.

Advanced strategies and tools to facilitate and streamline microbial adaptive laboratory evolution

Adaptive laboratory evolution (ALE) has served as a historic microbial engineering method that mimics natural selection to obtain desired microbes. The past decade has witnessed improvements in all aspects of ALE workflow, in terms of growth coupling, genotypic diversification, phenotypic selection, and genotype-phenotype mapping. The developing growth-coupling strategies facilitate ALE to a wider range of appealing traits. In vivo mutagenesis methods and multiplexed automated culture platforms open new gates to streamline its execution. Meanwhile, the application of multi-omics analyses and multiplexed genetic engineering promote efficient knowledge mining. This article provides a comprehensive and updated review of these advances, highlights newest significant applications, and discusses future improvements, aiming to provide a practical guide for implementation of novel, effective, and efficient ALE experiments.

Expanding the lysine industry: biotechnological production of l-lysine and its derivatives

l-lysine is an essential amino acid that contains various functional groups including α-amino, ω-amino, and α-carboxyl groups, exhibiting high reaction potential. The derivatization of these functional groups produces a series of value-added chemicals, such as cadaverine, glutarate, and d-lysine, that are widely applied in the chemical synthesis, cosmetics, food, and pharmaceutical industries. Here, we review recent advances in the biotechnological production of l-lysine and its derivatives and expatiate key technological strategies. Furthermore, we also discuss the existing challenges and potential strategies for more efficient production of these chemicals.

pyFOOMB: Python framework for object oriented modeling of bioprocesses

Quantitative characterization of biotechnological production processes requires the determination of different key performance indicators (KPIs) such as titer, rate and yield. Classically, these KPIs can be derived by combining black-box bioprocess modeling with non-linear regression for model parameter estimation. The presented pyFOOMB package enables a guided and flexible implementation of bioprocess models in the form of ordinary differential equation systems (ODEs). By building on Python as powerful and multi-purpose programing language, ODEs can be formulated in an object-oriented manner, which facilitates their modular design, reusability, and extensibility. Once the model is implemented, seamless integration and analysis of the experimental data is supported by various Python packages that are already available. In particular, for the iterative workflow of experimental data generation and subsequent model parameter estimation we employed the concept of replicate model instances, which are linked by common sets of parameters with global or local properties. For the description of multi-stage processes, discontinuities in the right-hand sides of the differential equations are supported via event handling using the freely available assimulo package. Optimization problems can be solved by making use of a parallelized version of the generalized island approach provided by the pygmo package. Furthermore, pyFOOMB in combination with Jupyter notebooks also supports education in bioprocess engineering and the applied learning of Python as scientific programing language. Finally, the applicability and strengths of pyFOOMB will be demonstrated by a comprehensive collection of notebook examples.

In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing

Reprogramming complex cellular metabolism requires simultaneous regulation of multigene expression. Ex-situ cloning-based methods are commonly used, but the target gene number and combinatorial library size are severely limited by cloning and transformation efficiencies. In-situ methods such as multiplex automated genome engineering (MAGE) depends on high-efficiency transformation and incorporation of heterologous DNA donors, which are limited to few microorganisms. Here, we describe a Base Editor-Targeted and Template-free Expression Regulation (BETTER) method for simultaneously diversifying multigene expression. BETTER repurposes CRISPR-guided base editors and in-situ generates large numbers of genetic combinations of diverse ribosome binding sites, 5’ untranslated regions, or promoters, without library construction, transformation, and incorporation of DNA donors. We apply BETTER to simultaneously regulate expression of up to ten genes in industrial and model microorganisms Corynebacterium glutamicum and Bacillus subtilis. Variants with improved xylose catabolism, glycerol catabolism, or lycopene biosynthesis are respectively obtained. This technology will be useful for large-scale fine-tuning of multigene expression in both genetically tractable and intractable microorganisms.

To obtain optimal yield and productivity in bioproduction, expression of pathway genes must be appropriately coordinated. Here, the authors report repurposing of base editors for simultaneous regulation of multiple gene expression and demonstrate its application in industrially important and model microorganisms.

Bacterial valorization of pulp and paper industry process streams and waste

The pulp and paper industry is a major source of lignocellulose-containing streams. The components of lignocellulose material are lignin, hemicellulose, and cellulose that may be hydrolyzed into their smaller components and used as feedstocks for valorization efforts. Much of this material is contained in underutilized streams and waste products, such as black liquor, pulp and paper sludge, and wastewater. Bacterial fermentation strategies have suitable potential to upgrade lignocellulosic biomass contained in these streams to value-added chemicals. Bacterial conversion allows for a sustainable and economically feasible approach to valorizing these streams, which can bolster and expand applications of the pulp and paper industry. This review discusses the composition of pulp and paper streams, bacterial isolates from process streams that can be used for lignocellulose biotransformations, and technological approaches for improving valorization efforts. KEY POINTS: • Reviews the conversion of pulp and paper industry waste by bacterial isolates. • Metabolic pathways for the breakdown of lignocellulose components. • Methods for isolating bacteria, determining value-added products, and increasing product yields.

Recent Progress on Chemical Production From Non-food Renewable Feedstocks Using Corynebacterium glutamicum

Due to the non-renewable nature of fossil fuels, microbial fermentation is considered a sustainable approach for chemical production using glucose, xylose, menthol, and other complex carbon sources represented by lignocellulosic biomass. Among these, xylose, methanol, arabinose, glycerol, and other alternative feedstocks have been identified as superior non-food sustainable carbon substrates that can be effectively developed for microbe-based bioproduction. Corynebacterium glutamicum is a model gram-positive bacterium that has been extensively engineered to produce amino acids and other chemicals. Recently, in order to reduce production costs and avoid competition for human food, C. glutamicum has also been engineered to broaden its substrate spectrum. Strengthening endogenous metabolic pathways or assembling heterologous ones enables C. glutamicum to rapidly catabolize a multitude of carbon sources. This review summarizes recent progress in metabolic engineering of C. glutamicum toward a broad substrate spectrum and diverse chemical production. In particularly, utilization of lignocellulosic biomass-derived complex hybrid carbon source represents the futural direction for non-food renewable feedstocks was discussed.

Multi-Faceted Systems Biology Approaches Present a Cellular Landscape of Phenolic Compound Inhibition in Saccharomyces cerevisiae

Synthetic biology has played a major role in engineering microbial cell factories to convert plant biomass (lignocellulose) to fuels and bioproducts by fermentation. However, the final product yield is limited by inhibition of microbial growth and fermentation by toxic phenolic compounds generated during lignocellulosic pre-treatment and hydrolysis. Advances in the development of systems biology technologies (genomics, transcriptomics, proteomics, metabolomics) have rapidly resulted in large datasets which are necessary to obtain a holistic understanding of complex biological processes underlying phenolic compound toxicity. Here, we review and compare different systems biology tools that have been utilized to identify molecular mechanisms that modulate phenolic compound toxicity in Saccharomyces cerevisiae. By focusing on and comparing functional genomics and transcriptomics approaches we identify common mechanisms potentially underlying phenolic toxicity. Additionally, we discuss possible ways by which integration of data obtained across multiple unbiased approaches can result in new avenues to develop yeast strains with a significant improvement in tolerance to phenolic fermentation inhibitors.

Current Status and Applications of Adaptive Laboratory Evolution in Industrial Microorganisms

Adaptive laboratory evolution (ALE) is an evolutionary engineering approach in artificial conditions that improves organisms through the imitation of natural evolution. Due to the development of multi-level omics technologies in recent decades, ALE can be performed for various purposes at the laboratory level. This review delineates the basics of the experimental design of ALE based on several ALE studies of industrial microbial strains and updates current strategies combined with progressed metabolic engineering, in silico modeling and automation to maximize the evolution efficiency. Moreover, the review sheds light on the applicability of ALE as a strain development approach that complies with non-recombinant preferences in various food industries. Overall, recent progress in the utilization of ALE for strain development leading to successful industrialization is discussed.

A combined experimental and modelling approach for the Weimberg pathway optimisation

The oxidative Weimberg pathway for the five-step pentose degradation to α-ketoglutarate is a key route for sustainable bioconversion of lignocellulosic biomass to added-value products and biofuels. The oxidative pathway from Caulobacter crescentus has been employed in in-vivo metabolic engineering with intact cells and in in-vitro enzyme cascades. The performance of such engineering approaches is often hampered by systems complexity, caused by non-linear kinetics and allosteric regulatory mechanisms. Here we report an iterative approach to construct and validate a quantitative model for the Weimberg pathway. Two sensitive points in pathway performance have been identified as follows: (1) product inhibition of the dehydrogenases (particularly in the absence of an efficient NAD⁺ recycling mechanism) and (2) balancing the activities of the dehydratases. The resulting model is utilized to design enzyme cascades for optimized conversion and to analyse pathway performance in C. cresensus cell-free extracts.

Metabolic engineering of carbohydrate metabolism systems in Corynebacterium glutamicum for improving the efficiency of L-lysine production from mixed sugar

The efficiency of industrial fermentation process mainly depends on carbon yield, final titer and productivity. To improve the efficiency of l-lysine production from mixed sugar, we engineered carbohydrate metabolism systems to enhance the effective use of sugar in this study. A functional metabolic pathway of sucrose and fructose was engineered through introduction of fructokinase from Clostridium acetobutylicum. l-lysine production was further increased through replacement of phosphoenolpyruvate-dependent glucose and fructose uptake system (PTS^Glc and PTS^Fru) by inositol permeases (IolT1 and IolT2) and ATP-dependent glucokinase (ATP-GlK). However, the shortage of intracellular ATP has a significantly negative impact on sugar consumption rate, cell growth and l-lysine production. To overcome this defect, the recombinant strain was modified to co-express bifunctional ADP-dependent glucokinase (ADP-GlK/PFK) and NADH dehydrogenase (NDH-2) as well as to inactivate SigmaH factor (SigH), thus reducing the consumption of ATP and increasing ATP regeneration. Combination of these genetic modifications resulted in an engineered C. glutamicum strain K-8 capable of producing 221.3 ± 17.6 g/L l-lysine with productivity of 5.53 g/L/h and carbon yield of 0.71 g/g glucose in fed-batch fermentation. As far as we know, this is the best efficiency of l-lysine production from mixed sugar. This is also the first report for improving the efficiency of l-lysine production by systematic modification of carbohydrate metabolism systems.

Recent Advances of L-ornithine Biosynthesis in Metabolically Engineered Corynebacterium glutamicum

L-ornithine, a valuable non-protein amino acid, has a wide range of applications in the pharmaceutical and food industries. Currently, microbial fermentation is a promising, sustainable, and environment-friendly method to produce L-ornithine. However, the industrial production capacity of L-ornithine by microbial fermentation is low and rarely meets the market demands. Various strategies have been employed to improve the L-ornithine production titers in the model strain, Corynebacterium glutamicum, which serves as a major indicator for improving the cost-effectiveness of L-ornithine production by microbial fermentation. This review focuses on the development of high L-ornithine-producing strains by metabolic engineering and reviews the recent advances in breeding strategies, such as reducing by-product formation, improving the supplementation of precursor glutamate, releasing negative regulation and negative feedback inhibition, increasing the supply of intracellular cofactors, modulating the central metabolic pathway, enhancing the transport system, and adaptive evolution for improving L-ornithine production.

Metabolic and evolutionary responses of Clostridium thermocellum to genetic interventions aimed at improving ethanol production

BACKGROUND

Engineering efforts targeted at increasing ethanol by modifying the central fermentative metabolism of Clostridium thermocellum have been variably successful. Here, we aim to understand this variation by a multifaceted approach including genomic and transcriptomic analysis combined with chemostat cultivation and high solids cellulose fermentation. Three strain lineages comprising 16 strains total were examined. Two strain lineages in which genes involved in pathways leading to organic acids and/or sporulation had been knocked out resulted in four end-strains after adaptive laboratory evolution (ALE). A third strain lineage recapitulated mutations involving adhE that occurred spontaneously in some of the engineered strains.

RESULTS

Contrary to lactate dehydrogenase, deleting phosphotransacetylase (pta, acetate) negatively affected steady-state biomass concentration and caused increased extracellular levels of free amino acids and pyruvate, while no increase in ethanol was detected. Adaptive laboratory evolution (ALE) improved growth and shifted elevated levels of amino acids and pyruvate towards ethanol, but not for all strain lineages. Three out of four end-strains produced ethanol at higher yield, and one did not. The occurrence of a mutation in the adhE gene, expanding its nicotinamide-cofactor compatibility, enabled two end-strains to produce more ethanol. A disruption in the hfsB hydrogenase is likely the reason why a third end-strain was able to make more ethanol. RNAseq analysis showed that the distribution of fermentation products was generally not regulated at the transcript level. At 120 g/L cellulose loadings, deletions of spo0A, ldh and pta and adaptive evolution did not negatively influence cellulose solubilization and utilization capabilities. Strains with a disruption in hfsB or a mutation in adhE produced more ethanol, isobutanol and 2,3-butanediol under these conditions and the highest isobutanol and ethanol titers reached were 5.1 and 29.9 g/L, respectively.

CONCLUSIONS

Modifications in the organic acid fermentative pathways in Clostridium thermocellum caused an increase in extracellular pyruvate and free amino acids. Adaptive laboratory evolution led to improved growth, and an increase in ethanol yield and production due a mutation in adhE or a disruption in hfsB. Strains with deletions in ldh and pta pathways and subjected to ALE demonstrated undiminished cellulolytic capabilities when cultured on high cellulose loadings.

FeedER: a feedback-regulated enzyme-based slow-release system for fed-batch cultivation in microtiter plates

With the advent of modern genetic engineering methods, microcultivation systems have become increasingly important tools for accelerated strain phenotyping and bioprocess engineering. While these systems offer sophisticated capabilities to screen batch processes, they lack the ability to realize fed-batch processes, which are used more frequently in industrial bioprocessing. In this study, a novel approach to realize a feedback-regulated enzyme-based slow-release system (FeedER), allowing exponential fed-batch for microscale cultivations, was realized by extending our existing Mini Pilot Plant technology with a customized process control system. By continuously comparing the experimental growth rates with predefined set points, the automated dosage of Amyloglucosidase enzyme for the cleavage of dextrin polymers into d-glucose monomers is triggered. As a prerequisite for stable fed-batch operation, a constant pH is maintained by automated addition of ammonium hydroxide. We show the successful application of FeedER to study fed-batch growth of different industrial model organisms including Corynebacterium glutamicum, Pichia pastoris, and Escherichia coli. Moreover, the comparative analysis of a C. glutamicum GFP producer strain, cultivated under microscale batch and fed-batch conditions, revealed two times higher product yields under slow growing fed-batch operation. In summary, FeedER enables to run 48 parallel fed-batch experiments in an automated and miniaturized manner, and thereby accelerates industrial bioprocess development at the screening stage.

The emergence of adaptive laboratory evolution as an efficient tool for biological discovery and industrial biotechnology

Harnessing the process of natural selection to obtain and understand new microbial phenotypes has become increasingly possible due to advances in culturing techniques, DNA sequencing, bioinformatics, and genetic engineering. Accordingly, Adaptive Laboratory Evolution (ALE) experiments represent a powerful approach both to investigate the evolutionary forces influencing strain phenotypes, performance, and stability, and to acquire production strains that contain beneficial mutations. In this review, we summarize and categorize the applications of ALE to various aspects of microbial physiology pertinent to industrial bioproduction by collecting case studies that highlight the multitude of ways in which evolution can facilitate the strain construction process. Further, we discuss principles that inform experimental design, complementary approaches such as computational modeling that help maximize utility, and the future of ALE as an efficient strain design and build tool driven by growing adoption and improvements in automation.

Multiscale dynamic modeling and simulation of a biorefinery

A biorefinery comprises a variety of process steps to synthesize products from sustainable natural resources. Dynamic plant‐wide simulation enhances the process understanding, leads to improved cost efficiency and enables model‐based operation and control. It is thereby important for an increased competitiveness to conventional processes. To this end, we developed a Modelica library with replaceable building blocks that allow dynamic modeling of an entire biorefinery. For the microbial conversion step, we built on the dynamic flux balance analysis (DFBA) approach to formulate process models for the simulation of cellular metabolism under changing environmental conditions. The resulting system of differential‐algebraic equations with embedded optimization criteria (DAEO) is solved by a tailor‐made toolbox. In summary, our modeling framework comprises three major pillars: A Modelica library of dynamic unit operations, an easy‐to‐use interface to formulate DFBA process models and a DAEO toolbox that allows simulation with standard environments based on the Modelica modeling language. A biorefinery model for dynamic simulation of the OrganoCat pretreatment process and microbial conversion of the resulting feedstock by Corynebacterium glutamicum serves as case study to demonstrate its practical relevance.