Metabolic Engineering Communications最新文献

Neutrophils are innate immune cells and the first line of defense for the maintenance of homeostasis. However, our knowledge of the metabolic rewiring associated with their differentiation and immune stimulation is limited. Here, quantitative ¹³C-metabolic flux analysis was performed using HL-60 cells as the neutrophil model. A metabolic model for ¹³C-metabolic flux analysis of neutrophils was developed based on the accumulation of ¹³C in intracellular metabolites derived from ¹³C-labeled extracellular carbon sources and intracellular macromolecules. Aspartate and glutamate in the medium were identified as carbon sources that enter central carbon metabolism. Furthermore, the breakdown of macromolecules, estimated to be fatty acids and nucleic acids, was observed. Based on these results, a modified metabolic model was used for ¹³C-metabolic flux analysis of undifferentiated, differentiated, and lipopolysaccharide (LPS)-activated HL-60 cells. The glucose uptake rate and glycolytic flux decreased with differentiation, whereas the tricarboxylic acid (TCA) cycle flux remained constant. The addition of LPS to differentiated HL-60 cells activated the glucose uptake rate and pentose phosphate pathway (PPP) flux levels, resulting in an increased rate of total NADPH regeneration, which could be used to generate reactive oxygen species. The flux levels of fatty acid degradation and synthesis were also increased in LPS-activated HL-60 cells. Overall, this study highlights the quantitative metabolic alterations in multiple pathways via the differentiation and activation of HL-60 cells using ¹³C-metabolic flux analysis.

Many desired biobased chemicals exhibit a range of toxicity to microbial cell factories, making industry-level biomanufacturing more challenging. Separating microbial growth and production phases is known to be beneficial for improving production of toxic products. Here, we developed a novel synthetic carbon-responsive promoter for use in the rapidly growing, stress-tolerant yeast Kluyveromyces marxianus, by fusing carbon-source responsive elements of the native ICL1 promoter to the strong S. cerevisiae TDH3 or native NC1 promoter cores. Two hybrids, P_IT350 and P_IN450, were validated via EGFP fluorescence and demonstrated exceptional strength, partial repression during growth, and late phase activation in glucose- and lactose-based medium, respectively. Expressing the Gerbera hybrida 2-pyrone synthase (2-PS) for synthesis of the polyketide triacetic acid lactone (TAL) under the control of P_IN450 increased TAL more than 50% relative to the native NC1 promoter, and additional promoter engineering further increased TAL titer to 1.39 g/L in tube culture. Expression of the Penicillium griseofulvum 6-methylsalicylic acid synthase (6-MSAS) under the control of P_IN450 resulted in a 6.6-fold increase in 6-MSA titer to 1.09 g/L and a simultaneous 1.5-fold increase in cell growth. Finally, we used P_IN450 to express the Pseudomonas savastanoi IaaM and IaaH proteins and the Salvia pomifera sabinene synthase protein to improve production of the auxin hormone indole-3-acetic acid and the monoterpene sabinene, respectively, both extremely toxic to yeast. The development of carbon-responsive promoters adds to the synthetic biology toolbox and available metabolic engineering strategies for K. marxianus, allowing greater control over heterologous protein expression and improved production of toxic metabolites.

Squalene is a highly sought-after triterpene compound in growing demand, and its production offers a promising avenue for circular economy practices. In this study, we applied metabolic engineering principles to enhance squalene production in the nonconventional yeast Yarrowia lipolytica, using waste cooking oil as a substrate. By overexpressing key enzymes in the mevalonate pathway — specifically ERG9 encoding squalene synthase, ERG20 encoding farnesyl diphosphate synthase, and HMGR encoding hydroxy-methyl-glutaryl-CoA reductase — we achieved a yield of 779.9 mg/L of squalene. Further co-overexpression of DGA1, encoding diacylglycerol acyltransferase, and CAT2, encoding carnitine acetyltransferase, in combination with prior metabolic enhancements, boosted squalene production to 1381.4 mg/L in the engineered strain Po1g17. To enhance the supply of the precursor acetyl-CoA and inhibit downstream squalene conversion, we supplemented with 6 g/L pyruvic acid and 0.7 mg/L terbinafine, resulting in an overall squalene titer of 2594.1 mg/L. These advancements underscore the potential for sustainable, large-scale squalene production using Y. lipolytica cell factories, contributing to circular economy initiatives by valorizing waste materials.

The microbial production of value-added chemicals from renewable feedstocks is an important step towards a sustainable, bio-based economy. Therefore, microbes need to efficiently utilize lignocellulosic biomass and its dominant constituents, such as d-xylose. Pseudomonas taiwanensis VLB120 assimilates d-xylose via the five-step Weimberg pathway. However, the knowledge about the metabolic constraints of the Weimberg pathway, i.e., its regulation, dynamics, and metabolite fluxes, is limited, which hampers the optimization and implementation of this pathway for bioprocesses. We characterized the Weimberg pathway activity of P. taiwanensis VLB120 in terms of biomass growth and the dynamics of pathway intermediates. In batch cultivations, we found excessive accumulation of the intermediates d-xylonolactone and d-xylonate, indicating bottlenecks in d-xylonolactone hydrolysis and d-xylonate uptake. Moreover, the intermediate accumulation was highly dependent on the concentration of d-xylose and the extracellular pH. To encounter the apparent bottlenecks, we identified and overexpressed two genes coding for putative endogenous xylonolactonases PVLB_05820 and PVLB_12345. Compared to the control strain, the overexpression of PVLB_12345 resulted in an increased growth rate and biomass generation of up to 30 % and 100 %, respectively. Next, d-xylonate accumulation was decreased by overexpressing two newly identified d-xylonate transporter genes, PVLB_18545 and gntP (PVLB_13665). Finally, we combined xylonolactonase overexpression with enhanced uptake of d-xylonate by knocking out the gntP repressor gene gntR (PVLB_13655) and increased the growth rate and biomass yield by 50 % and 24 % in stirred-tank bioreactors, respectively. Our study contributes to the fundamental knowledge of the Weimberg pathway in pseudomonads and demonstrates how to encounter the metabolic bottlenecks of the Weimberg pathway to advance strain developments and cell factory design for bioprocesses on renewable feedstocks.

Phenylpropenes are a class of natural products that are synthesised by a vast range of plant species and hold considerable promise in the flavour and fragrance industries. Many in vitro studies have been carried out to elucidate and characterise the enzymes responsible for the production of these volatile compounds. However, there is a scarcity of studies demonstrating the in vivo production of phenylpropenes in microbial cell factories. In this study, we engineered Escherichia coli to produce methylchavicol, methyleugenol and isoeugenol from their respective phenylacrylic acid precursors. We achieved this by extending and modifying a previously optimised heterologous pathway for the biosynthesis of chavicol and eugenol. We explored the potential of six S-adenosyl l-methionine (SAM)-dependent O-methyltransferases to produce methylchavicol and methyleugenol from chavicol and eugenol, respectively. Additionally, we examined two isoeugenol synthases for the production of isoeugenol from coniferyl acetate. The best-performing strains in this study were able to achieve titres of 13 mg L⁻¹ methylchavicol, 59 mg L⁻¹ methyleugenol and 361 mg L⁻¹ isoeugenol after feeding with their appropriate phenylacrylic acid substrates. We were able to further increase the methyleugenol titre to 117 mg L⁻¹ by supplementation with methionine to facilitate SAM recycling. Moreover, we report the biosynthesis of methylchavicol and methyleugenol from l-tyrosine through pathways involving six and eight enzymatic steps, respectively.

Methionine biosynthesis relies on the sequential catalysis of multiple enzymes. Escherichia coli, the main bacteria used in research and industry for protein production and engineering, utilizes the three-step trans-sulfurylation pathway catalyzed by L-homoserine O-succinyl transferase, cystathionine gamma synthase and cystathionine beta lyase to convert L-homoserine to L-homocysteine. However, most bacteria employ the two-step direct-sulfurylation pathway involving L-homoserine O-acetyltransferases and O-acetyl homoserine sulfhydrylase. We previously showed that a methionine-auxotroph Escherichia coli strain (MG1655) with deletion of metA, encoding for L-homoserine O-succinyl transferase, and metB, encoding for cystathionine gamma synthase, could be complemented by introducing the genes metX, encoding for L-homoserine O-acetyltransferases and metY, encoding for O-acetyl homoserine sulfhydrylase, from various sources, thus altering the Escherichia coli methionine biosynthesis metabolic pathway to direct-sulfurylation. However, introducing metX and metY from Corynebacterium glutamicum failed to complement methionine auxotrophy. Herein, we generated a randomized genetic library based on the metX and metY of Corynebacterium glutamicum and transformed it into a methionine-auxotrophic Escherichia coli strain lacking the metA and metB genes. Through multiple enrichment cycles, we successfully isolated active clones capable of growing in M9 minimal media. The dominant metX mutations in the evolved methionine-autotrophs Escherichia coli were L315P and H46R. Interestingly, we found that a metY gene encoding only the N-terminus 106 out of 438 amino acids of the wild-type MetY enzyme is functional and supports the growth of the methionine auxotroph. Recloning the new genes into the original plasmid and transforming them to methionine auxotroph Escherichia coli validated their functionality. These results show that directed enzyme-evolution enables fast and simultaneous engineering of new active variants within the Escherichia coli methionine direct-sulfurylation pathway, leading to efficient complementation.

The aldehyde 5-(hydroxymethyl)furfural (HMF) is of great importance for a circular bioeconomy. It is a renewable platform chemical that can be converted into a range of useful compounds to replace petroleum-based products such as the green plastic monomer 2,5-furandicarboxylic acid (FDCA). However, it also exhibits microbial toxicity for example hindering the efficient biotechnological valorization of lignocellulosic hydrolysates. Thus, there is an urgent need for tolerance-improved organisms applicable to whole-cell biocatalysis. Here, we engineer an oxidation-deficient derivative of the naturally robust and emerging biotechnological workhorse P. taiwanensis VLB120 by robotics-assisted adaptive laboratory evolution (ALE). The deletion of HMF-oxidizing enzymes enabled for the first time evolution under constant selection pressure by the aldehyde, yielding strains with consistently improved growth characteristics in presence of the toxicant. Genome sequencing of evolved clones revealed loss-of function mutations in the LysR-type transcriptional regulator-encoding mexT preventing expression of the associated efflux pump mexEF-oprN. This knowledge allowed reverse engineering of strains with enhanced aldehyde tolerance, even in a background of active or overexpressed HMF oxidation machinery, demonstrating a synergistic effect of two distinct tolerance mechanisms.

Kinetic models of metabolism are promising platforms for studying complex metabolic systems and designing production strains. Given the availability of enzyme kinetic data from historical experiments and machine learning estimation tools, a straightforward modeling approach is to assemble kinetic data enzyme by enzyme until a desired scale is reached. However, this type of ‘bottom up’ parameterization of kinetic models has been difficult due to a number of issues including gaps in kinetic parameters, the complexity of enzyme mechanisms, inconsistencies between parameters obtained from different sources, and in vitro-in vivo differences. Here, we present a computational workflow for the robust estimation of kinetic parameters for detailed mass action enzyme models while taking into account parameter uncertainty. The resulting software package, termed MASSef (the Mass Action Stoichiometry Simulation Enzyme Fitting package), can handle standard ‘macroscopic’ kinetic parameters, including K_m, k_cat, K_i, K_eq, and n_h, as well as diverse reaction mechanisms defined in terms of mass action reactions and ‘microscopic’ rate constants. We provide three enzyme case studies demonstrating that this approach can identify and reconcile inconsistent data either within in vitro experiments or between in vitro and in vivo enzyme function. We further demonstrate how parameterized enzyme modules can be used to assemble pathway-scale kinetic models consistent with in vivo behavior. This work builds on the legacy of knowledge on kinetic behavior of enzymes by enabling robust parameterization of enzyme kinetic models at scale utilizing the abundance of historical literature data and machine learning parameter estimates.

Cell based factories can be engineered to produce a wide variety of products. Advances in DNA synthesis and genome editing have greatly simplified the design and construction of these factories. It has never been easier to generate hundreds or even thousands of cell factory strain variants for evaluation. These advances have amplified the need for standardized, higher throughput means of evaluating these designs. Toward this goal, we have previously reported the development of engineered E. coli strains and associated 2-stage production processes to simplify and standardize strain engineering, evaluation and scale up. This approach relies on decoupling growth (stage 1), from production, which occurs in stationary phase (stage 2). Phosphate depletion is used as the trigger to stop growth as well as induce heterologous expression. Here, we describe in detail the development of protocols for the evaluation of engineered E. coli strains in 2-stage microfermentations. These protocols are readily adaptable to the evaluation of strains producing a wide variety of protein as well as small molecule products. Additionally, by detailing the approach to protocol development, these methods are also adaptable to additional cellular hosts, as well as other 2-stage processes with various additional triggers.

This paper reviews the key building blocks needed to develop a mechanistic model for use as an operational production tool. The Chinese Hamster Ovary (CHO) cell, one of the most widely used hosts for antibody production in the pharmaceutical industry, is considered as a case study. CHO cell metabolism is characterized by two main phases, exponential growth followed by a stationary phase with strong protein production. This process presents an appropriate degree of complexity to outline the modeling strategy. The paper is organized into four main steps: (1) CHO systems and data collection; (2) metabolic analysis; (3) formulation of the mathematical model; and finally, (4) numerical solution, calibration, and validation. The overall approach can build a predictive model of target variables. According to the literature, one of the main current modeling challenges lies in understanding and predicting the spontaneous metabolic shift. Possible candidates for the trigger of the metabolic shift include the concentration of lactate and carbon dioxide. In our opinion, ammonium, which is also an inhibiting product, should be further investigated. Finally, the expected progress in the emerging field of hybrid modeling, which combines the best of mechanistic modeling and machine learning, is presented as a fascinating breakthrough. Note that the modeling strategy discussed here is a general framework that can be applied to any bioprocess.