Metabolites That Confirm Induction and Release of Dormancy Phases in Sweet Cherry Buds

Here we report on metabolites found in a targeted profiling of 'Summit' flower buds for nine years, which could be indicators for the timing of endodormancy release (t₁) and beginning of ontogenetic development (t₁*). Investigated metabolites included chrysin, arabonic acid, pentose acid, sucrose, abscisic acid (ABA), and abscisic acid glucose ester (ABA-GE). Chrysin and water content showed an almost parallel course between leaf fall and t₁*. After 'swollen bud', water content raised from ~60 to ~80% at open cluster, while chrysin content decreased and lost its function as an acetylcholinesterase inhibitor. Both parameters can be suitable indicators for t₁*. Arabonic acid showed a clear increase after t₁*. Pentose acid would be a suitable metabolite to identify t₁ and t₁*, but would not allow describing the ecodormancy phase, because of its continuously low value during this time. Sucrose reached a maximum during ecodormancy and showed a significant correlation with air temperature, which confirms its cryoprotective role in this phase. The ABA content showed maximum values during endodormancy and decreased during ecodormancy, reaching 50% of its content t₁ at t₁*. It appears to be the key metabolite to define the ecodormancy phase. The ABA-GE was present at all stages and phases and was much higher than the ABA content and is a readily available storage pool in cherry buds.

Optimized Fast Filtration-Based Sampling and Extraction Enables Precise and Absolute Quantification of the Escherichia coli Central Carbon Metabolome

Precise and accurate quantification is a prerequisite for interpretation of targeted metabolomics data, but this task is challenged by the inherent instability of the analytes. The sampling, quenching, extraction, and sample purification conditions required to recover and stabilize metabolites in representative extracts have also been proven highly dependent on species-specific properties. For Escherichia coli, unspecific leakage has been demonstrated for conventional microbial metabolomics sampling protocols. We herein present a fast filtration-based sampling protocol for this widely applied model organism, focusing on pitfalls such as inefficient filtration, selective loss of biomass, matrix contamination, and membrane permeabilization and leakage. We evaluate the effect of and need for removal of extracellular components and demonstrate how residual salts can challenge analytical accuracy of hyphenated mass spectrometric analyses, even when sophisticated correction strategies are applied. Laborious extraction procedures are bypassed by direct extraction in cold acetonitrile:water:methanol (3:5:2, v/v%), ensuring compatibility with sample concentration and thus, any downstream analysis. By applying this protocol, we achieve and demonstrate high precision and low metabolite turnover, and, followingly, minimal perturbation of the inherent metabolic state. This allows us to herein report absolute intracellular concentrations in E. coli and explore its central carbon metabolome at several commonly applied cultivation conditions.

A comparative study at bioprocess and metabolite levels of superhost strain Streptomyces coelicolor M1152 and its derivative M1581 heterologously expressing chloramphenicol biosynthetic gene cluster

Microbial superhost strains should provide an ideal platform for the efficient homologous or heterologous phenotypic expression of biosynthetic gene clusters (BGCs) of new and novel bioactive molecules. Our aim in the current study was to perform a comparative study at the bioprocess and metabolite levels of the previously designed superhost strain Streptomyces coelicolor M1152 and its derivative strain S. coelicolor M1581 heterologously expressing chloramphenicol BGC. Parent strain M1152 was characterized by a higher specific growth rate, specific CO₂ evolution rate, and a higher specific l-glutamate consumption rate as compared with M1581. Intracellular primary central metabolites (nucleoside/sugar phosphates, amino acids, organic acids, and CoAs) were quantified using four targeted LC-MS/MS-based methods. The metabolite pathways in the nonantibiotic producing S. coelicolor host strain were flooded with carbon from both carbon sources, whereas in antibiotic-producing strain, the carbon of l-glutamate seems to be draining out through excreting synthesized antibiotic. The ¹³ C-isotope-labeling experiments revealed the bidirectionality in the glycolytic pathway and reversibility in the non-oxidative part of PPP even with continuous uptake of d-glucose. The change in the primary metabolites due to the insertion of BGC disclosed a clear linkage between the primary and secondary metabolites.

Targeted LC-MS/MS Profiling of Bile Acids in Various Animal Tissues

Bile acids are being increasingly investigated in humans and laboratory animals as markers for various diseases in addition to their important functions, such as promoting the emulsification in fat digestion and preventing gallstone formation. In humans and animals, primary bile acids are formed from cholesterol in the liver, converted in the intestine into various secondary bile acids by the intestinal microbiota and reabsorbed in the terminal ileum, and partially returned to the liver. A universal high-throughput workflow, including a simple workup, was applied as a tool for bile acid analysis in animal studies. The complex bile acid profiles in various tissues, organs, and body fluids from different animals were mapped using a newly developed comprehensive liquid chromatography-tandem mass spectrometry method. The method can also be used in screening food to obtain information about the nutritional content of bile acids. This could be relevant to investigations on various animal diseases and on the bioavailability of bile acids that pass through the gastric tract.

Development of a Highly Sensitive Ultra-High-Performance Liquid Chromatography Coupled to Electrospray Ionization Tandem Mass Spectrometry Quantitation Method for Fecal Bile Acids and Application on Crohn's Disease Studies

In addition to their important role in fat digestion, bile acids are increasingly being used as markers for various diseases. The large diversity of bile acids results from the conversion of primary and conjugated bile acids into secondary bile acids by deconjugation and dehydroxylation reactions mediated by the intestinal microbiota. Here, we describe a fast and sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for absolute quantitation of 45 bile acids in human or mouse feces in combination with a simple workup and extraction procedure. Method validation outlined excellent limits of detection and quantitation, linearity, selectivity, recovery, extraction loss, and precision. To investigate the connection between microbiome alterations and bile acid metabolism, the method was applied on a Crohn's disease study including patients with histologically documented active disease or remission as well as on a model using humanized mice. As the complex mechanism including genetic and environmental factors leading to the development of Crohn's disease is so far not completely understood, the study investigates the microbial metabolism of bile acids and the potential use of bile acid profiles to predict disease state.

UPLC-ESI-MRM/MS for Absolute Quantification and MS/MS Structural Elucidation of Six Specialized Pyranonaphthoquinone Metabolites From Ventilago harmandiana

Pyranonaphthoquinones (PNQs) are important structural scaffolds found in numerous natural products. Research interest in these specialized metabolites lies in their natural occurrence and therapeutic activities. Nonetheless, research progress has thus far been hindered by the lack of analytical standards and analytical methods for both qualitative and quantitative analysis. We report here that various parts of Ventilago harmandiana are rich sources of PNQs. We developed an ultraperformance liquid chromatography-electrospray ionization multiple reaction monitoring/mass spectrometry method to quantitatively determine six PNQs from leaves, root, bark, wood, and heartwood. The addition of standards in combination with a stable isotope of salicylic acid-D₆ was used to overcome the matrix effect with average recovery of 82% ± 1% (n = 15). The highest concentration of the total PNQs was found in the root (11,902 μg/g dry weight), whereas the lowest concentration was found in the leaves (28 μg/g dry weight). Except for the root, PNQ-332 was found to be the major compound in all parts of V. harmandiana, accounting for ∼48% of the total PNQs quantified in this study. However, PNQ-318A was the most abundant PNQ in the root sample, accounting for 27% of the total PNQs. Finally, we provide novel MS/MS spectra of the PNQs at different collision induction energies: 10, 20, and 40 eV (POS and NEG). For structural elucidation purposes, we propose complete MS/MS fragmentation pathways of PNQs using MS/MS spectra at collision energies of 20 and 40 eV. The MS/MS spectra along with our discussion on structural elucidation of these PNQs should be very useful to the natural products community to further exploring PNQs in V. harmandiana and various other sources.

Absolute Quantification of the Central Carbon Metabolome in Eight Commonly Applied Prokaryotic and Eukaryotic Model Systems

Absolute quantification of intracellular metabolite pools is a prerequisite for modeling and in-depth biological interpretation of metabolomics data. It is the final step of an elaborate metabolomics workflow, with challenges associated with all steps—from sampling to quantifying the physicochemically diverse metabolite pool. Chromatographic separation combined with mass spectrometric (MS) detection is the superior platform for high coverage, selective, and sensitive detection of metabolites. Herein, we apply our quantitative MS-metabolomics workflow to measure and present the central carbon metabolome of a panel of commonly applied biological model systems. The workflow includes three chromatographic methods combined with isotope dilution tandem mass spectrometry to allow for absolute quantification of 68 metabolites of glycolysis, the pentose phosphate pathway, the tricarboxylic acid cycle, and the amino acid and (deoxy) nucleoside pools. The biological model systems; Bacillus subtilis, Saccharomyces cerevisiae, two microalgal species, and four human cell lines were all cultured in commonly applied culture media and sampled in exponential growth phase. Both literature and databases are scarce with comprehensive metabolite datasets, and existing entries range over several orders of magnitude. The workflow and metabolite panel presented herein can be employed to expand the list of reference metabolomes, as encouraged by the metabolomics community, in a continued effort to develop and refine high-quality quantitative metabolomics workflows.

Transcript abundance on its own cannot be used to infer fluxes in central metabolism

An attempt has been made to define the extent to which metabolic flux in central plant metabolism is reflected by changes in the transcriptome and metabolome, based on an analysis of in vitro cultured immature embryos of two oilseed rape (Brassica napus) accessions which contrast for seed lipid accumulation. Metabolic flux analysis (MFA) was used to constrain a flux balance metabolic model which included 671 biochemical and transport reactions within the central metabolism. This highly confident flux information was eventually used for comparative analysis of flux vs. transcript (metabolite). Metabolite profiling succeeded in identifying 79 intermediates within the central metabolism, some of which differed quantitatively between the two accessions and displayed a significant shift corresponding to flux. An RNA-Seq based transcriptome analysis revealed a large number of genes which were differentially transcribed in the two accessions, including some enzymes/proteins active in major metabolic pathways. With a few exceptions, differential activity in the major pathways (glycolysis, TCA cycle, amino acid, and fatty acid synthesis) was not reflected in contrasting abundances of the relevant transcripts. The conclusion was that transcript abundance on its own cannot be used to infer metabolic activity/fluxes in central plant metabolism. This limitation needs to be borne in mind in evaluating transcriptome data and designing metabolic engineering experiments.