13C-Metabolic Flux Analysis Reveals Effect of Phenol on Central Carbon Metabolism in Escherichia coli

Simultaneous removal of ammonia nitrogen, phosphate, zinc, and phenol by degradation of cellulose in composite mycelial pellet bioreactor: Enhanced performance and community co-assembly mechanism

In this experiment, the prepared tea biochar-cellulose@LDH material (TB-CL@LDH) was combined with mycelium pellets to form the composite mycelial pellets (CMP), then assembled and immobilized with strains Pseudomonas sp. Y1 and Cupriavidus sp. ZY7 to construct a bioreactor. At the best operating parameters, the initial concentrations of phosphate (PO43--P), ammonia nitrogen (NH4+-N), chemical oxygen demand (COD), zinc (Zn2+), and phenol were 22.3, 25.0, 763.8, 1.0, and 1.0 mg L-1, the corresponding removal efficiencies were 80.4, 87.0, 83.4, 91.8, and 96.6%, respectively. Various characterization analyses demonstrated that the strain Y1 used the additional carbon source produced by the strain ZY7 degradation of cellulose to enhance the removal of composite pollutants and clarified the principle of Zn2+ and PO43--P removal by adsorption, co-precipitation and biomineralization. Pseudomonas and Cupriavidus were the dominant genera according to the high-throughput sequencing. As shown by KEGG results, nitrification and denitrification genes were affected by phenol. The study offers prospects for the simultaneous removal of complex pollutants consisting of NH4+-N, PO43--P, Zn2+, and phenol.

Diversity and function of viral AMGs associated with DNA biosynthesis in the Napahai plateau wetland

Viruses play an important role in microbial community structure and biodiversity by lysing host cells, and can also affect host metabolic pathways by expressing auxiliary metabolic genes (AMGs). As a unique low-latitude, high-altitude seasonal plateau wetland in China, Napahai has high research value. However, studies on the genetic diversity of AMGs and viruses associated with DNA biosynthesis have not been reported. Based on metagenomics, with the phylogenetic tree, PCoA, and α diversity analysis, we found that three DNA biosynthesis-related viral AMGs (cobS, mazG, and purM) in the Napahai plateau wetland were rich in genetic diversity, uniqueness, and differences compared with other habitats and host sources. Through the KEGG metabolic pathway and metabolic flow analysis of Pseudomonas mandelii (SW-3) and phage (VSW-3), the AMGs (cobS, mazG, and purM) genes of the three related viruses involved in DNA biosynthesis were upregulated and their expression increased significantly. In general, we systematically described the genetic diversity of AMGs associated with DNA biosynthesis in plateau wetland ecosystems and clarified the contribution of viral AMGs in the Napahai plateau wetland to DNA biosynthesis, as well as the changes of metabolites and genes. It further expands the understanding of phage-host interactions, which is of great significance for further revealing the role of viral AMGs in the biological evolution and biogeochemical cycle of wetland ecosystems.

GC/MS-based 13C metabolic flux analysis resolves the parallel and cyclic photomixotrophic metabolism of Synechocystis sp. PCC 6803 and selected deletion mutants including the Entner-Doudoroff and phosphoketolase pathways

BACKGROUND

Cyanobacteria receive huge interest as green catalysts. While exploiting energy from sunlight, they co-utilize sugar and CO₂. This photomixotrophic mode enables fast growth and high cell densities, opening perspectives for sustainable biomanufacturing. The model cyanobacterium Synechocystis sp. PCC 6803 possesses a complex architecture of glycolytic routes for glucose breakdown that are intertwined with the CO₂-fixing Calvin-Benson-Bassham (CBB) cycle. To date, the contribution of these pathways to photomixotrophic metabolism has remained unclear.

RESULTS

Here, we developed a comprehensive approach for ¹³C metabolic flux analysis of Synechocystis sp. PCC 6803 during steady state photomixotrophic growth. Under these conditions, the Entner-Doudoroff (ED) and phosphoketolase (PK) pathways were found inactive but the microbe used the phosphoglucoisomerase (PGI) (63.1%) and the oxidative pentose phosphate pathway (OPP) shunts (9.3%) to fuel the CBB cycle. Mutants that lacked the ED pathway, the PK pathway, or phosphofructokinases were not affected in growth under metabolic steady-state. An ED pathway-deficient mutant (Δeda) exhibited an enhanced CBB cycle flux and increased glycogen formation, while the OPP shunt was almost inactive (1.3%). Under fluctuating light, ∆eda showed a growth defect, different to wild type and the other deletion strains.

CONCLUSIONS

The developed approach, based on parallel ¹³C tracer studies with GC-MS analysis of amino acids, sugars, and sugar derivatives, optionally adding NMR data from amino acids, is valuable to study fluxes in photomixotrophic microbes to detail. In photomixotrophic cells, PGI and OPP form glycolytic shunts that merge at switch points and result in synergistic fueling of the CBB cycle for maximized CO₂ fixation. However, redirected fluxes in an ED shunt-deficient mutant and the impossibility to delete this shunt in a GAPDH2 knockout mutant, indicate that either minor fluxes (below the resolution limit of ¹³C flux analysis) might exist that could provide catalytic amounts of regulatory intermediates or alternatively, that EDA possesses additional so far unknown functions. These ideas require further experiments.

Microbe-assisted phytoremediation of environmental pollutants and energy recycling in sustainable agriculture

The perception of phytoremediation is efficiently utilized as an eco-friendly practice of green plants combating and cleaning up the stressed environment without harming it. The industrial revolution was followed by the green revolution which fulfilled the food demands of the growing population caused an increase in yield per unit area in crop production, but it also increased the use of synthetic fertilizers in agriculture. Globally, the intensive use of inorganic fertilizers in agriculture has led to serious health problems and irreversible environmental damage. Biofertilizers improve the growth of the plant and can be applied as an alternative to chemical/synthetic fertilizers. Cyanobacteria, bacteria, and fungi are known as some of the principal microbe groups used to produce biofertilizers that form symbiotic associations with plants. Microorganisms perform a key role in phosphate solubilization and mobilization, nitrogen fixation, nutrient management, biotic elicitors and probiotics, and pollution management (biodegradation agents), specifically bacteria which also help in atmospheric nitrogen fixation and are thus available for the growth of the plant. Management or biodegradation of hazardous chemical residues and heavy metals produced by a huge number of large-scale industries should be given primary importance to be transformed by various bacterial strains, fungi, algae. Currently, modern omics technologies such as metagenomic, transcriptomic, and proteomic are being used to develop strategies for studying the ecology of microorganisms, as well as their use in environmental monitoring and bioremediation. This review briefly discusses some of the major groups of microorganisms that can perform different functions responsible for plant health, crop production, phytoremediation and also focus on the omics techniques reportedly used in environmental monitoring to tackle the pollution load.

Method for high-efficiency fed-batch cultures of recombinant Escherichia coli

Fed-batch processes are commonly used in industry to obtain sufficient biomass and associated recombinant protein or plasmids. In research laboratories, it is more common to use batch cultures, as the setup of fed-batch processes can be challenging. This method outlines a robust and reliable means to generate Escherichia coli biomass in a minimum amount of fermentation time using a standardized fed-batch process. Final cell densities can reach over 50g dry cell weight per liter (gdcw/L) depending on the strain. This method uses a predefined exponential feeding strategy and conservative induction protocol to achieve these targets without multiple trial and error studies. If desired, productivity can be optimized by balancing the induction time and feed rates. This method utilizes cost-efficient defined media, minimizes process control complexity, and potentially aids downstream purification.

Recent advances in constraint and machine learning-based metabolic modeling by leveraging stoichiometric balances, thermodynamic feasibility and kinetic law formalisms

Understanding the governing principles behind organisms' metabolism and growth underpins their effective deployment as bioproduction chassis. A central objective of metabolic modeling is predicting how metabolism and growth are affected by both external environmental factors and internal genotypic perturbations. The fundamental concepts of reaction stoichiometry, thermodynamics, and mass action kinetics have emerged as the foundational principles of many modeling frameworks designed to describe how and why organisms allocate resources towards both growth and bioproduction. This review focuses on the latest algorithmic advancements that have integrated these foundational principles into increasingly sophisticated quantitative frameworks.

Identification of a rate-limiting step in a metabolic pathway using the kinetic model and in vitro experiment

Identification of the rate-limiting step in a metabolic pathway is an important challenge in metabolic engineering for enhancing pathway flow. Although specific enzyme activities (V_max) provide valuable clues for the identification, it is time-consuming and difficult to measure multiple enzymes in the pathway because different assay protocols are required for each enzyme. In the present study, we propose a method to simultaneously determine the V_max values of multiple enzymes using a kinetic model with a time course of the intermediate concentrations through an in vitro experiment. To demonstrate this method, nine glycolysis reactions for converting glucose-6-phosphate (G6P) to pyruvate in Escherichia coli were considered. In a reaction mixture containing G6P and cofactors, glycolysis was initiated by adding a crude cell extract obtained from stationary phase cells. The V_max values were optimized to minimize the difference between the measured and simulated time-courses using a kinetic model. Metabolic control analysis using the kinetic model with the estimated V_max values revealed that fructose bisphosphate aldolase (FBA) was the rate-limiting step in the upper part of glycolysis. The addition of FBA in the reaction mixture successfully increased the glycolytic flux in vitro. Furthermore, in vivo, the specific glucose consumption rate of an FBA overexpression strain was 1.4 times higher than that of the control strain during the stationary phase. These results confirmed that FBA was the rate-limiting step in glycolysis under the stationary phase. This approach provides V_max values of multiple enzymes in a pathway for metabolic control analysis with a kinetic model.

Metabolic Engineering Design Strategies for Increasing Acetyl-CoA Flux

Acetyl-CoA is a key metabolite precursor for the biosynthesis of lipids, polyketides, isoprenoids, amino acids, and numerous other bioproducts which are used in various industries. Metabolic engineering efforts aim to increase carbon flux towards acetyl-CoA in order to achieve higher productivities of its downstream products. In this review, we summarize the strategies that have been implemented for increasing acetyl-CoA flux and concentration, and discuss their effects. Furthermore, recent works have developed synthetic acetyl-CoA biosynthesis routes that achieve higher stoichiometric yield of acetyl-CoA from glycolytic substrates.