Optimization Of Metabolic Pathways Research Articles

Improved consolidated bioprocessing for itaconic acid production by simultaneous optimization of cellulase and metabolic pathway of Neurospora crassa

Lignocellulose was directly used in itaconic acid production by a model filamentous fungus Neurospora crassa. The promoters of two clock control genes and cellobiohydrolase 1 gene were selected for heterologous genes expression by evaluating different types of promoters. The effect of overexpression of different cellulase was compared, and it was found that expression of cellobiohydrolase 2 from Trichoderma reesei increased the filter paper activity by 2 times, the cellobiohydrolase activity by 4.5 times, and that the itaconic acid titer was also significantly improved. A bidirectional cis-aconitic acid accumulation strategy was established by constructing the reverse glyoxylate shunt and expressing the transporter MTTA, which increased itaconic acid production to 637.2 mg/L. The simultaneous optimization of cellulase and metabolic pathway was more conducive to the improvement of cellulase activity than that of cellulase alone, so as to further increase itaconic acid production. Finally, through the combination of fermentation by optimized strains and medium optimization, the titers of itaconic acid using Avicel and corn stover as substrate were 1165.1 mg/L and 871.3 mg/L, respectively. The results prove the potential of the consolidated bioprocessing that directly converts lignocellulose to itaconic acid by a model cellulase synthesizing strain.

Enhanced bacterial cellulose production in Komagataeibacter sucrofermentans: impact of different PQQ-dependent dehydrogenase knockouts and ethanol supplementation

BackgroundBacterial cellulose (BC) is a biocompatible material with unique mechanical properties, thus holding a significant industrial potential. Despite many acetic acid bacteria (AAB) being BC overproducers, cost-effective production remains a challenge. The role of pyrroloquinoline quinone (PQQ)-dependent membrane dehydrogenases (mDH) is crucial in the metabolism of AAB since it links substrate incomplete oxidation in the periplasm to energy generation. Specifically, glucose oxidation to gluconic acid substantially lowers environmental pH and hinders BC production. Conversely, ethanol supplementation is known to enhance BC yields in Komagataeibacter spp. by promoting efficient glucose utilization.ResultsK. sucrofermentans ATCC 700178 was engineered, knocking out the four PQQ-mDHs, to assess their impact on BC production. The strain KS003, lacking PQQ-dependent glucose dehydrogenase (PQQ-GDH), did not produce gluconic acid and exhibited a 5.77-fold increase in BC production with glucose as the sole carbon source, and a 2.26-fold increase under optimal ethanol supplementation conditions. In contrast, the strain KS004, deficient in the PQQ-dependent alcohol dehydrogenase (PQQ-ADH), showed no significant change in BC yield in the single carbon source experiment but showed a restrained benefit from ethanol supplementation.ConclusionsThe results underscore the critical influence of PQQ-GDH and PQQ-ADH and clarify the effect of ethanol supplementation on BC production in K. sucrofermentans ATCC 700178. This study provides a foundation for further metabolic pathway optimization, emphasizing the importance of diauxic ethanol metabolism for high BC production.

Flux optimization using multiple promoters in Halomonas bluephagenesis as a model chassis of the next generation industrial biotechnology

Predictability and robustness are challenges for bioproduction because of the unstable intracellular synthetic activities. With the deeper understanding of the gene expression process, fine-tuning has become a meaningful tool for biosynthesis optimization. This study characterized several gene expression elements and constructed a multiple inducible system that responds to ten different small chemical inducers in halophile bacterium Halomonas bluephagenesis. Genome insertion of regulators was conducted for the purpose of gene cluster stabilization and regulatory plasmid simplification. Additionally, dynamic ranges of the multiple inducible systems were tuned by promoter sequence mutations to achieve diverse scopes for high-resolution gene expression control. The multiple inducible system was successfully employed to precisely control chromoprotein expression, lycopene and poly-3-hydroxybutyrate (PHB) biosynthesis, resulting in colorful bacterial pictures, optimized cell growth, lycopene and PHB accumulation. This study demonstrates a desirable approach for fine-tuning of rational and efficient gene expressions, displaying the significance for metabolic pathway optimization.

Recent Progress in Metabolic Engineering of Escherichia coli for the Production of Various C4 and C5-Dicarboxylic Acids.

As an alternative to petrochemical synthesis, well-established industrial microbes, such as Escherichia coli, are employed to produce a wide range of chemicals, including dicarboxylic acids (DCAs), which have significant potential in diverse areas including biodegradable polymers. The demand for biodegradable polymers has been steadily rising, prompting the development of efficient production pathways on four- (C4) and five-carbon (C5) DCAs derived from central carbon metabolism to meet the increased demand via the biosynthesis. In this context, E. coli is utilized to produce these DCAs through various metabolic engineering strategies, including the design or selection of metabolic pathways, pathway optimization, and enhancement of catalytic activity. This review aims to highlight the recent advancements in metabolic engineering techniques for the production of C4 and C5 DCAs in E. coli.

Co-production of 7-chloro-tryptophan and indole pyruvic acid based on an efficient FAD/FADH2 regeneration system.

Efficient FAD/FADH2 regeneration is vital for enzymatic biocatalysis and metabolic pathway optimization. Here, we constructed an efficient and simple FAD/FADH2 regeneration system through a combination of L-amino acid deaminase (L-AAD) and halogenase (CombiAADHa), which was applied for catalyzing the conversion of an L-amino acid to halide and an α-keto acid. For cell-free biotransformation, the optimal activity ratio of L-AAD and halogenase was set between 1:50 and 1:60. Within 6h, 170mg/L of 7-chloro-tryptophan (7-Cl-Trp) and 193mg/L of indole pyruvic acid (IPA) were synthesized in the selected mono-amino acid system. For whole-cell biotransformation, 7-Cl-Trp and IPA synthesis was enhanced by 15% (from 96 to 110mg/L) and 12% (from 115 to 129mg/L), respectively, through expression fine-tuning and the strengthening of FAD/FADH2 supply. Finally, ultrasound treatment was applied to improve membrane permeability and adjust the activity ratio, resulting in 1.6-and 1.4-fold higher 7-Cl-Trp and IPA yields. The products were then purified. This system could also be applied to the synthesis of other halides and α-keto acids. KEY POINTS: • In this study, a whole cell FAD/FADH2 regeneration system co-expressingl-AAD and halogenase was constructed • This study found that the activity and ratio of enzyme and the concentration of cofactors had a significant effect on the catalytic process for the efficient co-production of 7-chlorotryptophan and indole pyruvate.

Genetic engineering strategies for sustainable polyhydroxyalkanoate (PHA) production from carbon-rich wastes

Polyhydroxyalkanoates (PHAs) are promising biopolymers for biomedical applications due to their excellent biocompatibility and biodegradability. However, the high production cost mainly resulting from the pure sugar substrate limits PHA commercialization. It makes various carbon-rich wastes potential substrates for PHA production. The integration and optimization of metabolic pathways can further enhance the conversion of carbon-rich wastes to PHAs. Genetic engineering strategies focusing on carbon flux and energy metabolism have improved the PHA production capacities of targeted strains by promoting substrate assimilation, enhancing PHA synthesis, and reducing branch metabolism. CRISPR/Cas9-based systems have also served as efficient genome editing tools to improve the efficiency of metabolic modification. Genetic modification requires fitness among strains, substrates, and products. Therefore, this review outlined various efficient genetic engineering approaches to promote PHA production and discussed their feasibility in valorizing representative carbon-rich wastes. To further illustrate the widespread applicability of metabolic modification to support microbial cell factories with core PHA production, this review also involved advanced fermentation approaches and co-production systems for PHA production by engineered strains.

CRISPR-dCas12a-mediated genetic circuit cascades for multiplexed pathway optimization.

The production efficiency of microbial cell factories is sometimes limited by the lack of effective methods to regulate multiple targets in a coordinated manner. Here taking the biosynthesis of glucosamine-6-phosphate (GlcN6P) in Bacillus subtilis as an example, a 'design-build-test-learn' framework was proposed to achieve efficient multiplexed optimization of metabolic pathways. A platform strain was built to carry biosensor signal-amplifying circuits and two genetic regulation circuits. Then, a synthetic CRISPR RNA array blend for boosting and leading (ScrABBLE) device was integrated into the platform strain, which generated 5,184 combinatorial assemblies targeting three genes. The best GlcN6P producer was screened and engineered for the synthesis of valuable pharmaceuticals N-acetylglucosamine and N-acetylmannosamine. The N-acetylglucosamine titer reached 183.9 g liter-1 in a 15-liter bioreactor. In addition, the potential generic application of the ScrABBLE device was also verified using three fluorescent proteins as a case study.

Machine learning for metabolic pathway optimization: A review

Optimizing the metabolic pathways of microbial cell factories is essential for establishing viable biotechnological production processes. However, due to the limited understanding of the complex setup of cellular machinery, building efficient microbial cell factories remains tedious and time-consuming. Machine learning (ML), a powerful tool capable of identifying patterns within large datasets, has been used to analyze biological datasets generated using various high-throughput technologies to build data-driven models for complex bioprocesses. In addition, ML can also be integrated with Design–Build–Test–Learn to accelerate development. This review focuses on recent ML applications in genome-scale metabolic model construction, multistep pathway optimization, rate-limiting enzyme engineering, and gene regulatory element designing. In addition, we have discussed some limitations of these methods as well as potential solutions.

Cell-free metabolic engineering enables selective biotransformation of fatty acids to value-added chemicals

Fatty acid-derived products such as alkanes, fatty aldehydes, and fatty alcohols have many applications in the chemical industry. These products are predominately produced from fossil resources, but their production processes are often not environmentally friendly. While microbes like Escherichia coli have been engineered to convert fatty acids to corresponding products, the design and optimization of metabolic pathways in cells for high productivity is challenging due to low mass transfer, heavy metabolic burden, and intermediate/product toxicity. Here, we describe an E. coli-based cell-free protein synthesis (CFPS) platform for in vitro conversion of long-chain fatty acids to value-added chemicals with product selectivity, which can also avoid the above issues when using microbial production systems. We achieve the selective biotransformation by cell-free expression of different enzymes and the use of different conditions (e.g., light and heating) to drive the biocatalysis toward different final products. Specifically, in response to blue light, cell-free expressed fatty acid photodecarboxylase (CvFAP, a photoenzyme) was able to convert fatty acids to alkanes with approximately 90% conversion. When the expressed enzyme was switched to carboxylic acid reductase (CAR), fatty acids were reduced to corresponding fatty aldehydes, which, however, could be further reduced to fatty alcohols by endogenous reductases in the cell-free system. By using a thermostable CAR and a heating treatment, the endogenous reductases were deactivated and fatty aldehydes could be selectively accumulated (>97% in the product mixture) without over-reduction to alcohols. Overall, our cell-free platform provides a new strategy to convert fatty acids to valuable chemicals with notable properties of operation flexibility, reaction controllability, and product selectivity.

Tackling the Catch-22 Situation of Optimizing a Sensor and a Transporter System in a Whole-Cell Microbial Biosensor Design for an Anthropogenic Small Molecule.

Whole-cell biosensors provide a convenient detection tool for the high-throughput screening of genetically engineered biocatalytic activity. But establishing a biosensor for an anthropogenic molecule requires both a custom transporter and a transcription factor. This results in an unavoidable "Catch-22" situation in which transporter activity cannot be easily confirmed without a biosensor and a biosensor cannot be established without a functional transporter in a host organism. We overcame this type of circular problem while developing an adipic acid (ADA) sensor. First, leveraging an established cis,cis-muconic acid (ccMA) sensor, an annotated ccMA transporter MucK, which is expected to be broadly responsive to dicarboxylates, was stably expressed in the genome of Pseudomonas putida to function as a transporter for ADA, and then a PcaR transcription factor (endogenous to the strain and naturally induced by β-ketoadipic acid, BKA) was diversified and selected to detect the ADA molecule. While MucK expression is otherwise very unstable in P. putida under strong promoter expression, our optimized mucK expression was functional for over 70 generations without loss of function, and we selected an ADA sensor that showed a specificity switch of over 35-fold from BKA at low concentrations (typically <0.1 mM of inducers). Our ADA and BKA biosensors show high sensitivity (low detection concentration <10 μM) and dynamic range (∼50-fold) in an industrially relevant organism and will open new avenues for high throughput discovery and optimization of enzymes and metabolic pathways for the biomanufacture of these molecules. In particular, the novel ADA sensor will aid the discovery and evolution of efficient biocatalysts for the biological recycling of ADA from the degradation of nylon-6,6 waste.

Modular Engineering to Enhance Keratinase Production for Biotransformation of Discarded Feathers.

Biotransformation of wasted feathers via feather-degrading enzyme has gained immense popularity, low conversion efficiency hinders its scale application, and the main purpose of this study is to improve feather-degrading enzyme production in Bacillus licheniformis. Firstly, keratinase from Bacillus amyloliquefaciens K11 was attained with the best performance for feather hydrolysis, via screening several extracellular proteases from Bacillus; also, feather powder was proven as the most suitable substrate for determination of feather-degrading enzyme activity. Then, expression elements, including signal peptides and promoters, were optimized, and the combination of signal peptide SPSacC with promoter Pdual3 owned the best performance, keratinase activity aggrandized by 6.21-fold. According to amino acid compositions of keratinase and feeding assays, Ala, Val, and Ser were proven as critical precursors, and strengthening these precursors' supplies via metabolic pathway optimization resulted in a 33.59% increase in the keratinase activity. Furthermore, keratinase activity reached 2210.66 U/mL, up to 56.74-fold from the original activity under the optimized fermentation condition in 3-L fermentor. Finally, the biotransformation process of discarded feathers by the fermented keratinase was optimized, and our results indicated that 90.94% of discarded feathers (16%, w/v) were decomposed in 12h. Our results suggested that strengthening precursor amino acids' supplies was an efficient strategy for enhanced production of keratinase, and this research provided an efficient strain as well as the biotransformation process for discarded feather re-utilization.

Euglena International Network (EIN): Driving euglenoid biotechnology for the benefit of a challenged world.

Euglenoids (Euglenida) are unicellular flagellates possessing exceptionally wide geographical and ecological distribution. Euglenoids combine a biotechnological potential with a unique position in the eukaryotic tree of life. In large part these microbes owe this success to diverse genetics including secondary endosymbiosis and likely additional sources of genes. Multiple euglenoid species have translational applications and show great promise in production of biofuels, nutraceuticals, bioremediation, cancer treatments and more exotically as robotics design simulators. An absence of reference genomes currently limits these applications, including development of efficient tools for identification of critical factors in regulation, growth or optimization of metabolic pathways. The Euglena International Network (EIN) seeks to provide a forum to overcome these challenges. EIN has agreed specific goals, mobilized scientists, established a clear roadmap (Grand Challenges), connected academic and industry stakeholders and is currently formulating policy and partnership principles to propel these efforts in a coordinated and efficient manner.

Kinetic-model-based pathway optimization with application to reverse glycolysis in mammalian cells.

Over the last two decades, model-based metabolic pathway optimization tools have been developed for the design of microorganisms to produce desired metabolites. However, few have considered more complex cellular systems such as mammalian cells, which requires the use of nonlinear kinetic models to capture the effects of concentration changes and cross-regulatory interactions. In this study, we develop a new two-stage pathway optimization framework based on kinetic models that incorporate detailed kinetics and regulation information. In Stage 1, a set of optimization problems are solved to identify and rank the enzymes that contribute the most to achieving the metabolic objective. Stage 2 then determines the optimal enzyme interventions for specified desired numbers of enzyme adjustments. It also incorporates multi-scenario optimization, which allows the simultaneous consideration of multiple physiological conditions. We apply the proposed framework to find enzyme adjustments that enable a reverse glucose flow in cultured mammalian cells, thereby eliminating the need for glucose feed in the late culture stage and enhancing process robustness. The computational results demonstrate the efficacy of the proposed approach; it not only captures the important regulations and key enzymes for reverse glycolysis but also identifies differences and commonalities in the metabolic requirements for different carbon sources.

Even allocation of benefits stabilizes microbial community engaged in metabolic division of labor.

Microbial communities execute metabolic pathways to drive global nutrient cycles. Within a community, functionally specialized strains can perform different yet complementary steps within a linear pathway, a phenomenon termed metabolic division of labor (MDOL). However, little is known about how such metabolic behaviors shape microbial communities. Here, we derive a theoretical framework to define the assembly of a community that degrades an organic compound through MDOL. The framework indicates that to ensure community stability, the strains performing the initial steps should hold a growth advantage (m) over the "private benefit" (n) of the strain performing the last step. The steady-state frequency of the last strain is then determined by the quotient of n and m. Our experiments show that the framework accurately predicts the assembly of our synthetic consortia that degrade naphthalene through MDOL. Our results provide insights for designing and managing stable microbial systems for metabolic pathway optimization.

A review on microbial synthesis of lactate-containing polyesters.

Degradable polylactic acids (PLA) have been widely used in agriculture, textile, medicine and degradable plastics industry, and can completely replace petroleum-based plastics in the future. At present, polylactic acid was chemically synthesized by ring-opening polymerisation or the direct polycondensation of lactic acid, which inevitably leads to chemical and heavy metal catalyst pollution. The current research focus has gradually shifted to the development of recombinant industrial strains for the efficiently production of lactate-containing polyesters from renewable resources. This review summarizes various explorations of metabolic pathway optimization and production cost control in the industrialization of lactate-containing polyesters bio-production. In particular, the effects of key enzymes, including CoA transferase, polyhydroxyalkanoate synthase, and their mutants, culture conditions, low-cost carbon sources, and recombinant strains on the yield and composition of lactate-containing polyesters are summarized and discussed. Future prospects and challenges for the industrialization of lactate-containing polyesters are also pointed out.

Revisiting Theoretical Tools and Approaches for the Valorization of Recalcitrant Lignocellulosic Biomass to Value-Added Chemicals

Biorefinery processes for converting lignocellulosic biomass to fuels and chemicals proceed via an integrated series of steps. Biomass is first pretreated and deconstructed using chemical catalysts and/or enzymes to liberate sugar monomers and lignin fragments. Deconstruction is followed by a conversion step in which engineered host organisms assimilate the released sugar monomers and lignin fragments, and produce value-added fuels and chemicals. Over the past couple of decades, a significant amount of work has been done to develop innovative biomass deconstruction and conversion processes that efficiently solubilize biomass, separate lignin from the biomass, maximize yields of bioavailable sugars and lignin fragments and convert the majority of these carbon sources into fuels, commodity chemicals, and materials. Herein, we advocate that advanced in silico approaches provide a theoretical framework for developing efficient processes for lignocellulosic biomass valorization and maximizing yields of sugars and lignin fragments during deconstruction and fuel and chemical titers during conversion. This manuscript surveys the latest developments in lignocellulosic biomass valorization with special attention given to highlighting computational approaches used in process optimization for lignocellulose pretreatment; enzyme engineering for enhanced saccharification and delignification; and prediction of the genome modification necessary for desired pathway fine-tuning to upgrade products from biomass deconstruction into value-added products. Physics-based modeling approaches such as density functional theory calculations and molecular dynamics simulations have been most impactful in studies aimed at exploring the molecular level details of solvent-biomass interactions, reaction mechanisms occurring in biomass-solvent systems, and the catalytic mechanisms and engineering of enzymes involved in biomass degradation. More recently, with ever increasing amounts of data from, for example, advanced mutli-omics experiments, machine learning approaches have begun to make important contributions in synthetic biology and optimization of metabolic pathways for production of biofuels and chemicals.

Recent Advances in Directed Yeast Genome Evolution.

Saccharomyces cerevisiae, as a Generally Recognized as Safe (GRAS) fungus, has become one of the most widely used chassis cells for industrial applications and basic research. However, owing to its complex genetic background and intertwined metabolic networks, there are still many obstacles that need to be overcome in order to improve desired traits and to successfully link genotypes to phenotypes. In this context, genome editing and evolutionary technology have rapidly progressed over the last few decades to facilitate the rapid generation of tailor-made properties as well as for the precise determination of relevant gene targets that regulate physiological functions, including stress resistance, metabolic-pathway optimization and organismal adaptation. Directed genome evolution has emerged as a versatile tool to enable researchers to access desired traits and to study increasingly complicated phenomena. Here, the development of directed genome evolutions in S. cerevisiae is reviewed, with a focus on different techniques driving evolutionary engineering.

Ammonium-assimilating microbiome: A halophilic biosystem rationally optimized by carbon to nitrogen ratios with stable nitrogen conversion and microbial structure

The contradiction between theoretical metabolism of ammonium assimilation and experiential understanding of conventional biosystems makes the rational optimization of the ammonium-assimilating microbiome through carbon to nitrogen (C/N) ratios perplexing. The effect of different C/N ratios on ammonium-assimilating biosystems was investigated in saline wastewater treatment. C/N ratios significantly hindered the nutrient removal efficiency, but ammonium-assimilating biosystems maintained functional stability in nitrogen conversions and microbial communities. With sufficient biomass, higher than 86% ammonium and 73% phosphorus were removed when C/N ratios were higher than 25. Ammonium assimilation dominated the nitrogen metabolism in all biosystems even under relatively low C/N ratios, evidenced by the extremely low abundances of nitrification functional genes. Different C/N ratios did not significantly change the bacterial community structure of ammonium-assimilating biosystems. It is anticipated that the ammonium-assimilating biosystem with advantages of clear metabolic pathway and easy optimization can be applied to nutrient removal and recovery in saline environments.

Converting Sugars into Cannabinoids—The State-of-the-Art of Heterologous Production in Microorganisms

The legal cannabis market worldwide is facing new challenges regarding innovation in the production of cannabinoid-based drugs. The usual cannabinoid production involves growing Cannabis sativa L. outdoor or in dedicated indoor growing facilities, followed by isolation and purification steps. This process is limited by the growth cycles of the plant, where the cannabinoid content can deeply vary from each harvest. A game change approach that does not involve growing a single plant has gained the attention of the industry: cannabinoids fermentation. From recombinant yeasts and bacteria, researchers are able to reproduce the biosynthetic pathway to generate cannabinoids, such as (-)-Δ9-tetrahydrocannabinol (Δ9-THC), cannabidiol (CBD), and (-)-Δ9-tetrahydrocannabivarin (Δ9-THCV). This approach avoids pesticides, and natural resources such as water, land, and energy are reduced. Compared to growing cannabis, fermentation is a much faster process, although its limitation regarding the phytochemical broad range of molecules naturally present in cannabis. So far, there is not a consolidated process for this brand-new approach, being an emerging and promising concept for countries in which cultivation of Cannabis sativa L. is illegal. This survey discusses the techniques and microorganisms already established to accomplish the task and those yet in seeing for the future, exploring upsides and limitations about metabolic pathways, toxicity, and downstream recovery of cannabinoids throughout heterologous production. Therapeutic potential applications of cannabinoids and in silico methodology toward optimization of metabolic pathways are also explored. Moreover, conceptual downstream analysis is proposed to illustrate the recovery and purification of cannabinoids through the fermentation process, and a patent landscape is presented to provide the state-of-the-art of the transfer of knowledge from the scientific sphere to the industrial application.

Plant-Derived Cell-Free Biofactories for the Production of Secondary Metabolites.

Cell-free expression systems enable the production of proteins and metabolites within a few hours or days. Removing the cellular context while maintaining the protein biosynthesis apparatus provides an open system that allows metabolic pathways to be installed and optimized by expressing different numbers and combinations of enzymes. This facilitates the synthesis of secondary metabolites that are difficult to produce in cell-based systems because they are toxic to the host cell or immediately converted into downstream products. Recently, we developed a cell-free lysate derived from tobacco BY-2 cell suspension cultures for the production of recombinant proteins. This system is remarkably productive, achieving yields of up to 3 mg/mL in a one-pot in vitro transcription–translation reaction and contains highly active energy and cofactor regeneration pathways. Here, we demonstrate for the first time that the BY-2 cell-free lysate also allows the efficient production of several classes of secondary metabolites. As case studies, we synthesized lycopene, indigoidine, betanin, and betaxanthins, which are useful in the food, cosmetic, textile, and pharmaceutical industries. Production was achieved by the co-expression of up to three metabolic enzymes. For all four products, we achieved medium to high yields. However, the yield of betanin (555 μg/mL) was outstanding, exceeding the level reported in yeast cells by a factor of more than 30. Our results show that the BY-2 cell-free lysate is suitable not only for the verification and optimization of metabolic pathways, but also for the efficient production of small to medium quantities of secondary metabolites.