Engineering improved ethylene production: Leveraging systems biology and adaptive laboratory evolution.

Ethylene is a small hydrocarbon gas widely used in the chemical industry. Annual worldwide production currently exceeds 150 million tons, producing considerable amounts of CO2 contributing to climate change. The need for a sustainable alternative is therefore imperative. Ethylene is natively produced by several different microorganisms, including Pseudomonas syringae pv. phaseolicola via a process catalyzed by the ethylene-forming enzyme (EFE), subsequent heterologous expression of EFE has led to ethylene production in non-native bacterial hosts including Escherichia coli and cyanobacteria. However, solubility of EFE and substrate availability remain rate-limiting steps in biological ethylene production. We employed a combination of genome-scale metabolic modelling, continuous fermentation, and protein evolution to enable the accelerated development of a high efficiency ethylene producing E. coli strain, yielding a 49-fold increase in production, the most significant improvement reported to date. Furthermore, we have clearly demonstrated that this increased yield resulted from metabolic adaptations that were uniquely linked to EFE (wild type versus mutant). Our findings provide a novel solution to deregulate metabolic bottlenecks in key pathways, which can be readily applied to address other engineering challenges.

Quantitative Bioreactor Monitoring of Intracellular Bacterial Metabolites in Clostridium autoethanogenum Using Liquid Chromatography-Isotope Dilution Mass Spectrometry.

We report a liquid chromatography-isotope dilution mass spectrometry method for the simultaneous quantification of 131 intracellular bacterial metabolites of Clostridium autoethanogenum. A comprehensive mixture of uniformly 13C-labeled internal standards (U-13C IS) was biosynthesized from the closely related bacterium Clostridium pasteurianum using 4% 13C-glucose as a carbon source. The U-13C IS mixture combined with 12C authentic standards was used to validate the linearity, precision, accuracy, repeatability, limits of detection, and quantification for each metabolite. A robust-fitting algorithm was employed to reduce the weight of the outliers on the quantification data. The metabolite calibration curves were linear with R 2 ≥ 0.99, limits of detection were ≤1.0 µM, limits of quantification were ≤10 µM, and precision/accuracy was within RSDs of 15% for all metabolites. The method was subsequently applied for the daily monitoring of the intracellular metabolites of C. autoethanogenum during a CO gas fermentation over 40 days as part of a study to optimize biofuel production. The concentrations of the metabolites were estimated at steady states of different pH levels using the robust-fitting mathematical approach, and we demonstrate improved accuracy of results compared to conventional regression. Metabolic pathway analysis showed that reactions of the incomplete (branched) tricarboxylic acid "cycle" were the most affected pathways associated with the pH shift in the bioreactor fermentation of C. autoethanogenum and the concomitant changes in ethanol production.

Phospholipid-Gold Nanorods Induce Energy Crisis in MCF-7 Cells: Cytotoxicity Evaluation Using LC-MS-Based Metabolomics Approach.

Phospholipid-modified gold nanorods (phospholipid-GNRs) have demonstrated drastic cytotoxicity towards MCF-7 breast cancer cells compared to polyethylene glycol-coated GNRs (PEG-GNRs). In this study, the mechanism of cytotoxicity of phospholipid-GNRs towards MCF-7 cells was investigated using mass spectrometry-based global metabolic profiling and compared to PEGylated counterparts. The results showed that when compared to PEG-GNRs, phospholipid-GNRs induced significant and more pronounced impact on the metabolic profile of MCF-7 cells. Phospholipid-GNRs significantly decreased the levels of metabolic intermediates and end-products associated with cellular energy metabolisms resulting in dysfunction in TCA cycle, a reduction in glycolytic activity, and imbalance of the redox state. Additionally, phospholipid-GNRs disrupted several metabolism pathways essential for the normal growth and proliferation of cancer cells including impairment in purine, pyrimidine, and glutathione metabolisms accompanied by lower amino acid pools. On the other hand, the effects of PEG-GNRs were limited to alteration of glycolysis and pyrimidine metabolism. The current work shed light on the importance of metabolomics as a valuable analytical approach to explore the molecular effects of GNRs with different surface chemistry on cancer cell and highlights metabolic targets that might serve as promising treatment strategy in cancer.

Metabolic characterisation of Magnetospirillum gryphiswaldense MSR-1 using LC-MS-based metabolite profiling.

Magnetosomes are nano-sized magnetic nanoparticles with exquisite properties that can be used in a wide range of healthcare and biotechnological applications. They are biosynthesised by magnetotactic bacteria (MTB), such as Magnetospirillum gryphiswaldense MSR-1 (Mgryph). However, magnetosome bioprocessing yields low quantities compared to chemical synthesis of magnetic nanoparticles. Therefore, an understanding of the intracellular metabolites and metabolic networks related to Mgryph growth and magnetosome formation are vital to unlock the potential of this organism to develop improved bioprocesses. In this work, we investigated the metabolism of Mgryph using untargeted metabolomics. Liquid chromatography-mass spectrometry (LC-MS) was performed to profile spent medium samples of Mgryph cells grown under O2-limited (n = 6) and O2-rich conditions (n = 6) corresponding to magnetosome- and non-magnetosome producing cells, respectively. Multivariate, univariate and pathway enrichment analyses were conducted to identify significantly altered metabolites and pathways. Rigorous metabolite identification was carried out using authentic standards, the Mgryph-specific metabolite database and MS/MS mzCloud database. PCA and OPLS-DA showed clear separation and clustering of sample groups with cross-validation values of R2X = 0.76, R2Y = 0.99 and Q2 = 0.98 in OPLS-DA. As a result, 50 metabolites linked to 45 metabolic pathways were found to be significantly altered in the tested conditions, including: glycine, serine and threonine; butanoate; alanine, aspartate and glutamate metabolism; aminoacyl-tRNA biosynthesis and; pyruvate and citric acid cycle (TCA) metabolisms. Our findings demonstrate the potential of LC-MS to characterise key metabolites in Mgryph and will contribute to further understanding the metabolic mechanisms that affect Mgryph growth and magnetosome formation.

Quantitative Isotope-Dilution High-Resolution-Mass-Spectrometry Analysis of Multiple Intracellular Metabolites in Clostridium autoethanogenum with Uniformly 13C-Labeled Standards Derived from Spirulina.

We have investigated the applicability of commercially available lyophilized spirulina ( Arthrospira platensis), a microorganism uniformly labeled with 13C, as a readily accessible source of multiple 13C-labeled metabolites suitable as internal standards for the quantitative determination of intracellular bacterial metabolites. Metabolites of interest were analyzed by hydrophilic-interaction liquid chromatography coupled with high-resolution mass spectrometry. Multiple internal standards obtained from uniformly (U)-13C-labeled extracts from spirulina were used to enable isotope-dilution mass spectrometry (IDMS) in the identification and quantification of intracellular metabolites. Extraction of the intracellular metabolites of Clostridium autoethanogenum using 2:1:1 chloroform/methanol/water was found to be the optimal method in comparison with freeze-thaw, homogenization, and sonication methods. The limits of quantification were ≤1 µM with excellent linearity for all of the calibration curves ( R2 ≥ 0.99) for 74 metabolites. The precision and accuracy were found to be within relative standard deviations (RSDs) of 15% for 49 of the metabolites and within RSDs of 20% for all of the metabolites. The method was applied to study the effects of feeding different levels of carbon monoxide (as a carbon source) on the central metabolism and Wood-Ljungdahl pathway of C. autoethanogenum grown in continuous culture over 35 days. Using LC-IDMS with U-13C spirulina allowed the successful quantification of 52 metabolites in the samples, including amino acids, carboxylic acids, sugar phosphates, purines, and pyrimidines. The method provided absolute quantitative data on intracellular metabolites that was suitable for computational modeling to understand and optimize the C. autoethanogenum metabolic pathways active in gas fermentation.