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Abstract Background Genome-scale metabolic models (GEMs) serve as effective tools for understanding cellular phenotypes and predicting engineering targets in the development of industrial strain. Enzyme-constrained genome-scale metabolic models (ecGEMs) have emerged as a valuable advancement, providing more accurate predictions and unveiling new engineering targets compared to models lacking enzyme constraints. In 2022, a stoichiometric GEM, iDL1450, was reconstructed for the industrially significant fungus Myceliophthora thermophila. To enhance the GEM’s performance, an ecGEM was developed for M. thermophila in this study. Results Initially, the model iDL1450 underwent refinement and updates, resulting in a new version named iYW1475. These updates included adjustments to biomass components, correction of gene-protein-reaction (GPR) rules, and a consensus on metabolites. Subsequently, the first ecGEM for M. thermophila was constructed using machine learning-based k cat data predicted by TurNuP within the ECMpy framework. During the construction, three versions of ecGEMs were developed based on three distinct k cat collection methods, namely AutoPACMEN, DLKcat and TurNuP. After comparison, the ecGEM constructed using TurNuP-predicted k cat values performed better in several aspects and was selected as the definitive version of ecGEM for M. thermophila (ecMTM). Comparing ecMTM to iYW1475, the solution space was reduced and the growth simulation results more closely resembled realistic cellular phenotypes. Metabolic adjustment simulated by ecMTM revealed a trade-off between biomass yield and enzyme usage efficiency at varying glucose uptake rates. Notably, hierarchical utilization of five carbon sources derived from plant biomass hydrolysis was accurately captured and explained by ecMTM. Furthermore, based on enzyme cost considerations, ecMTM successfully predicted reported targets for metabolic engineering modification and introduced some new potential targets for chemicals produced in M. thermophila. Conclusions In this study, the incorporation of enzyme constraint to iYW1475 not only improved prediction accuracy but also broadened the model’s applicability. This research demonstrates the effectiveness of integrating of machine learning-based k cat data in the construction of ecGEMs especially in situations where there is limited measured enzyme kinetic parameters for a specific organism.

Abstract Regulation of amino acid’s biosynthetic pathway is of significant importance to maintain homeostasis and cell functions. Amino acids regulate their biosynthetic pathway by end-product feedback inhibition of enzymes catalyzing committed steps of a pathway. Discovery of new feedback resistant enzyme variants to enhance industrial production of amino acids is a key objective in industrial biotechnology. Deregulation of feedback inhibition has been achieved for various enzymes using in vitro and in silico mutagenesis techniques. As enzyme’s function, its substrate binding capacity, catalysis activity, regulation and stability are dependent on its structural characteristics, here, we provide detailed structural analysis of all feedback sensitive enzyme targets in amino acid biosynthetic pathways. Current review summarizes information regarding structural characteristics of various enzyme targets and effect of mutations on their structures and functions especially in terms of deregulation of feedback inhibition. Furthermore, applicability of various experimental as well as computational mutagenesis techniques to accomplish feedback resistance has also been discussed in detail to have an insight into various aspects of research work reported in this particular field of study.

Abstract Background Acetoin, especially the optically pure (3S)- or (3R)-enantiomer, is a high-value-added bio-based platform chemical and important potential pharmaceutical intermediate. Over the past decades, intense efforts have been devoted to the production of acetoin through green biotechniques. However, efficient and economical methods for the production of optically pure acetoin enantiomers are rarely reported. Previously, we systematically engineered the GRAS microorganism Corynebacterium glutamicum to efficiently produce (3R)-acetoin from glucose. Nevertheless, its yield and average productivity were still unsatisfactory for industrial bioprocesses. Results In this study, cellular carbon fluxes in the acetoin producer CGR6 were further redirected toward acetoin synthesis using several metabolic engineering strategies, including blocking anaplerotic pathways, attenuating key genes of the TCA cycle and integrating additional copies of the alsSD operon into the genome. Among them, the combination of attenuation of citrate synthase and inactivation of phosphoenolpyruvate carboxylase showed a significant synergistic effect on acetoin production. Finally, the optimal engineered strain CGS11 produced a titer of 102.45 g/L acetoin with a yield of 0.419 g/g glucose at a rate of 1.86 g/L/h in a 5 L fermenter. The optical purity of the resulting (3R)-acetoin surpassed 95%. Conclusion To the best of our knowledge, this is the highest titer of highly enantiomerically enriched (3R)-acetoin, together with a competitive product yield and productivity, achieved in a simple, green processes without expensive additives or substrates. This process therefore opens the possibility to achieve easy, efficient, economical and environmentally-friendly production of (3R)-acetoin via microbial fermentation in the near future.

Background: Poly(3-hydroxybutyrate) (PHB), have been considered to be good candidates for completely biodegradable polymers due to their similar mechanical properties to petroleum-derived polymers and complete biodeg-radability. Escherichia coli has been used to simulate the distribution of metabolic fluxes in recombinant £ coli producing poly(3-hydroxybutyrate) (PHB). Genome-scale metabolic network analysis can reveal unexpected metabolic engineering strategies to improve the production of biochemicals and biofuels. Results: In this study, we reported the discovery of a new pathway called threonine bypass by flux balance analysis of the genome-scale metabolic model off. coli. This pathway, mainly containing the reactions for threonine synthesis and degradation, can potentially increase the yield of PHB and other acetyl-CoA derived products by reutilizing the CO2 released at the pyruvate dehydrogenase step. To implement the threonine bypass for PHB production in £ coli, we deregulated the threonine and serine degradation pathway and enhanced the threonine synthesis, resulting in 2.23-fold improvement of PHB titer. Then, we overexpressed glyA to enhance the conversion of glycine to serine and activated transhydrogenase to generate NADPH required in the threonine bypass. Conclusions: The result strain TB17 (pBHR68) produced 6.82 g/L PHB with the yield of 0.36 g/g glucose in the shake flask fermentation and 35.92 g/L PHB with the yield of 0.23 g/g glucose in the fed-batch fermentation, which was almost 3.3-fold higher than the parent strain. The work outlined here shows that genome-scale metabolic network analysis can reveal novel metabolic engineering strategies for developing efficient microbial cell factories. [ABSTRACT FROM AUTHOR]

Background: The overexpression of key enzymes in a metabolic pathway is a frequently used genetic engineering strategy for strain improvement. Metabolic control analysis has been proposed to quantitatively determine key enzymes. However, the lack of quality data often makes it difficult to correctly identify key enzymes through control analysis. Here, we proposed a method combining in vitro metabolic pathway analysis and proteomics measurement to find the key enzymes in threonine synthesis pathway. Results: All enzymes in the threonine synthesis pathway were purified for the reconstruction and perturbation of the in vitro pathway. Label-free proteomics technology combined with APEX (absolute protein expression measurements) data analysis method were employed to determine the absolute enzyme concentrations in the crude enzyme extract obtained from a threonine production strain during the fastest threonine production period. The flux control coefficient of each enzyme in the pathway was then calculated by measuring the flux changes after titration of the corresponding enzyme. The isoenzyme LysC catalyzing the first step in the pathway has the largest flux control coefficient, and thus its concentration change has the biggest impact on pathway flux. To verify that the key enzyme identified through in vitro pathway analysis is also the key enzyme in vivo, we overexpressed LysC in the original threonine production strain. Fermentation results showed that the threonine concentration was increased 30% and the yield was increased 20%. Conclusions: In vitro metabolic pathways simulating in vivo cells can be built based on precise measurement of enzyme concentrations through proteomics technology and used for the determination of key enzymes through metabolic control analysis. This provides a new way to find gene overexpression targets for industrial strain improvement. [ABSTRACT FROM AUTHOR]

Background Poly(3-hydroxybutyrate) (PHB), a biodegradable bio-plastic, is one of the most common homopolymer of polyhydroxyalkanoates (PHAs). PHB is synthesized by a variety of microorganisms as intracellular carbon and energy storage compounds in response to environmental stresses. Bio-based production of PHB from renewable feedstock is a promising and sustainable alternative to the petroleum-based chemical synthesis of plastics. In this study, a novel strategy was applied to improve the PHB biosynthesis from different carbon sources. Results In this research, we have constructed E. coli strains to produce PHB by engineering the Serine-Deamination (SD) pathway, the Entner-Doudoroff (ED) pathway, and the pyruvate dehydrogenase (PDH) complex. Firstly, co-overexpression of sdaA (encodes L-serine deaminase), L-serine biosynthesis genes and pgk (encodes phosphoglycerate kinase) activated the SD Pathway, and the resulting strain SD02 (pBHR68), harboring the PHB biosynthesis genes from Ralstonia eutropha, produced 4.86 g/L PHB using glucose as the sole carbon source, representing a 2.34-fold increase compared to the reference strain. In addition, activating the ED pathway together with overexpressing the PDH complex further increased the PHB production to 5.54 g/L with content of 81.1% CDW. The intracellular acetyl-CoA concentration and the [NADPH]/[NADP+] ratio were enhanced after the modification of SD pathway, ED pathway and the PDH complex. Meanwhile, these engineering strains also had a significant increase in PHB concentration and content when xylose or glycerol was used as carbon source. Conclusions Significant levels of PHB biosynthesis from different kinds of carbon sources can be achieved by engineering the Serine-Deamination pathway, Entner-Doudoroff pathway and pyruvate dehydrogenase complex in E. coli JM109 harboring the PHB biosynthesis genes from Ralstonia eutropha. This work demonstrates a novel strategy for improving PHB production in E. coli. The strategy reported here should be useful for the bio-based production of PHB from renewable resources. [ABSTRACT FROM AUTHOR]