Sugar phosphate analysis with baseline separation and soft ionization by gas chromatography-negative chemical ionization-mass spectrometry improves flux estimation of bidirectional reactions in cancer cells

Highly Defective Zirconium-Based Metal-Organic Frameworks for the Efficient Adsorption and Detection of Sugar Phosphates in the Biological Sample

Enrichment and quantification of sugar phosphates (SPx) in biological samples were of great significance in biological medicine. In this work, a series of zirconium-based metal-organic frameworks (MOFs) with different degrees of defects, namely, HP-UiO-66-NH2-X, were synthesized using acetic acid as a modulator and were utilized as high-capacity adsorbents for the adsorption of SPx in biological samples. The results indicated that the addition of acetic acid altered the morphology of HP-UiO-66-NH2-X, with corresponding changes in pore size (3.99-9.28 nm) and specific surface area (894.44-1142.50 m2·g-1). HP-UiO-66-NH2-10 showed the outstanding performance by achieving complete adsorption of all four SPx using only 80 μg of the adsorbent. The excellent adsorption efficiency of HP-UiO-66-NH2-10 was also obtained with a wide pH range and short adsorption time (10 min). Adsorption experiments demonstrated that the adsorption process involved chemical adsorption and multilayer adsorption. By utilizing X-ray photoelectron spectroscopy and density functional theory to explain the adsorption mechanism, it was found that various interactions (including coordination, hydrogen bonding, and electrostatic interactions) collectively contributed to the exceptional adsorption capability of HP-UiO-66-NH2-10. Those results indicated that the defect strategy not only increased the specific surface area and pore size, providing additional adsorption sites, but also reduced the adsorption energy between HP-UiO-66-NH2-10 and SPx. Moreover, HP-UiO-66-NH2-10 showed a low limit of detection (0.001-0.01 ng·mL-1), high precision (<13.77%), and accuracy (80.10-111.83%) in serum, liver, and cells, good stability, high selectivity (SPx/glucose, 1:100 molar ratio), and high adsorption capacity (292 mg·g-1 for SPx). The practical detection of SPx from human serum was also verified, prefiguring the great potentials of defective zirconium-based MOFs for the enrichment and detection of SPx in the biological medicine.

Advances in Chromatographic and Mass Spectrometric Techniques for Analyzing Reducing Monosaccharides and Their Phosphates in Biological Samples

Reducing monosaccharides and their phosphates are critical metabolites in the central carbon metabolism pathway of living organisms. Variations in their content can indicate abnormalities in metabolic pathways and the onset of certain diseases, necessitating their analysis and detection. Reducing monosaccharides and their phosphates exhibit significant variations in content within biological samples and are present in many isomers, which makes the accurate quantification of reducing monosaccharides and their phosphates in biological samples a challenging task. Various analytical methods such as spectroscopy, fluorescence detection, colorimetry, nuclear magnetic resonance spectroscopy, sensor-based techniques, chromatography, and mass spectrometry are employed to detect monosaccharides and phosphates. In comparison, chromatography and mass spectrometry are highly favored for their ability to simultaneously analyze multiple components and their high sensitivity and selectivity. This review thoroughly evaluates the current chromatographic and mass spectrometric methods used for detecting reducing monosaccharides and their phosphates from 2013 to 2023, highlighting their efficacy and the advancements in these analytical technologies.

13C-metabolic flux analysis reveals metabolic rewiring in HL-60 neutrophil-like cells through differentiation and immune stimulation

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.

Research of saccharides and related biocomplexes: A review with recent techniques and applications

Saccharides and biocompounds as saccharide (sugar) complexes have various roles and biological functions in living organisms due to modifications via nucleophilic substitution, polymerization, and complex formation reactions. Mostly, mono-, di-, oligo-, and polysaccharides are stabilized to inactive glycosides, which are formed in metabolic pathways. Natural saccharides are important in food and environmental monitoring. Glycosides with various functionalities are significant in clinical and medical research. Saccharides are often studied with the chromatographic methods of hydrophilic interaction liquid chromatography and anion exchange chromatograpy, but also with capillary electrophoresis and mass spectrometry with their on-line coupling systems. Sample preparation is important in the identification of saccharide compounds. The cases discussed here focus on bioscience, clinical, and food applications.

ChREBP is activated by reductive stress and mediates GCKR-associated metabolic traits

Common genetic variants in glucokinase regulator (GCKR), which encodes GKRP, a regulator of hepatic glucokinase (GCK), influence multiple metabolic traits in genome-wide association studies (GWASs), making GCKR one of the most pleiotropic GWAS loci in the genome. It is unclear why. Prior work has demonstrated that GCKR influences the hepatic cytosolic NADH/NAD+ ratio, also referred to as reductive stress. Here, we demonstrate that reductive stress is sufficient to activate the transcription factor ChREBP and necessary for its activation by the GKRP-GCK interaction, glucose, and ethanol. We show that hepatic reductive stress induces GCKR GWAS traits such as increased hepatic fat, circulating FGF21, and circulating acylglycerol species, which are also influenced by ChREBP. We define the transcriptional signature of hepatic reductive stress and show its upregulation in fatty liver disease and downregulation after bariatric surgery in humans. These findings highlight how a GCKR-reductive stress-ChREBP axis influences multiple human metabolic traits.

Bayesian 13C-Metabolic Flux Analysis of Parallel Tracer Experiments in Granulocytes: A Directional Shift within the Non-Oxidative Pentose Phosphate Pathway Supports Phagocytosis

The pentose phosphate pathway (PPP) plays a key role in the cellular regulation of immune function; however, little is known about the interplay of metabolic adjustments in granulocytes, especially regarding the non-oxidative PPP. For the determination of metabolic mechanisms within glucose metabolism, we propose a novel set of measures for 13C-metabolic flux analysis based on ex vivo parallel tracer experiments ([1,2-13C]glucose, [U-13C]glucose, [4,5,6-13C]glucose) and gas chromatography-mass spectrometry labeling measurements of intracellular metabolites, such as sugar phosphates and their fragments. A detailed constraint analysis showed that the permission range for net and irreversible fluxes was limited to a three-dimensional space. The overall workflow, including its Bayesian flux estimation, resulted in precise flux distributions and pairwise confidence intervals, some of which could be represented as a line due to the strength of their correlation. The principal component analysis that was enabled by these behaviors comprised three components that explained 99.6% of the data variance. It showed that phagocytic stimulation reversed the direction of non-oxidative PPP net fluxes from ribose-5-phosphate biosynthesis toward glycolytic pathways. This process was closely associated with the up-regulation of the oxidative PPP to promote the oxidative burst.

First proof-of-concept of UC/HILIC for extending the versatility of the current art of supercritical fluid separation

Supercritical Fluid Chromatography (SFC), a high-throughput separation technique, has been widely applied as a promising routine method in pharmaceutical, pesticides, and metabolome analysis in the same way as conventional liquid chromatography and gas chromatography. Unified chromatography (UC), an advanced version of SFC, which applied gradient elution with mobile phase changing continuously from supercritical to subcritical and to liquid states, can further extend the SFC applications. UC mostly applying the popular mobile phase of 95%:5%/Methanol:Water with additives allows to analyze many hydrophilic compounds. However, many of phosphorylated metabolites or multi carboxylic acids show very poor peak shapes or even can't be eluted under UC conditions, thus hampering the UC's metabolome coverage. In this study, we proposed the first proof-of-concept of UC/HILIC, a novel strategy to extend the current UC metabolome coverage by employing an aqueous gradient right after the UC gradient on a single packed column in a single measurement. The proposed method showed significant improvement regarding the chromatographic performance and metabolome coverage, while still maintaining the precision and high throughput in comparison with conventional UC methods.

Metabolomics and modelling approaches for systems metabolic engineering

Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.

An Arabidopsis GCMS chemical ionization technique to quantify adaptive responses in central metabolism

We present a methodology to survey central metabolism in 13CO2-labeled Arabidopsis (Arabidopsis thaliana) rosettes by ammonia positive chemical ionization-gas chromatography-mass spectrometry. This technique preserves the molecular ion cluster of methyloxime/trimethylsilyl-derivatized analytes up to 1 kDa, providing unambiguous nominal mass assignment of >200 central metabolites and 13C incorporation rates into a subset of 111 from the tricarboxylic acid (TCA) cycle, photorespiratory pathway, amino acid metabolism, shikimate pathway, and lipid and sugar metabolism. In short-term labeling assays, we observed plateau labeling of ∼35% for intermediates of the photorespiratory cycle except for glyoxylate, which reached only ∼4% labeling and was also present at molar concentrations several fold lower than other photorespiratory intermediates. This suggests photorespiratory flux may involve alternate intermediate pools besides the generally accepted route through glyoxylate. Untargeted scans showed that in illuminated leaves, noncyclic TCA cycle flux and citrate export to the cytosol revert to a cyclic flux mode following methyl jasmonate (MJ) treatment. MJ also caused a block in the photorespiratory transamination of glyoxylate to glycine. Salicylic acid treatment induced the opposite effects in both cases, indicating the antagonistic relationship of these defense signaling hormones is preserved at the metabolome level. We provide complete chemical ionization spectra for 203 Arabidopsis metabolites from central metabolism, which uniformly feature the unfragmented pseudomolecular ion as the base peak. This unbiased, soft ionization technique is a powerful screening tool to identify adaptive metabolic trends in photosynthetic tissue and represents an important advance in methodology to measure plant metabolic flux.

Isotope Calculation Gadgets: A Series of Software for Isotope-Tracing Experiments in Garuda Platform

Isotope tracing is a powerful technique for elucidating intracellular metabolism. Experiments utilizing this technique involve various processes, such as the correction of natural isotopes. Although some previously developed software are available for these procedures, there are still time-consuming steps in isotope tracing including the creation of an isotope measurement method in mass spectrometry (MS) and the interpretation of obtained labeling data. Additionally, these multi-step tasks often require data format conversion, which is also time-consuming. In this study, the Isotope Calculation Gadgets, a series of software that supports an entire workflow of isotope-tracing experiments, was developed in the Garuda platform, an open community. Garuda is a graphical user interface-based platform that allows individual operations to be sequentially performed, without data format conversion, which significantly reduces the required time and effort. The developed software includes new features that construct channels for isotopomer measurements, as well as conventional functions such as natural isotope correction, the calculation of fractional labeling and split ratio, and data mapping, thus facilitating an overall workflow of isotope-tracing experiments through smooth functional integration.

Quantitative metabolic fluxes regulated by trans-omic networks

Cells change their metabolism in response to internal and external conditions by regulating the trans-omic network, which is a global biochemical network with multiple omic layers. Metabolic flux is a direct measure of the activity of a metabolic reaction that provides valuable information for understanding complex trans-omic networks. Over the past decades, techniques to determine metabolic fluxes, including 13C-metabolic flux analysis (13C-MFA), flux balance analysis (FBA), and kinetic modeling, have been developed. Recent studies that acquire quantitative metabolic flux and multi-omic data have greatly advanced the quantitative understanding and prediction of metabolism-centric trans-omic networks. In this review, we present an overview of 13C-MFA, FBA, and kinetic modeling as the main techniques to determine quantitative metabolic fluxes, and discuss their advantages and disadvantages. We also introduce case studies with the aim of understanding complex metabolism-centric trans-omic networks based on the determination of metabolic fluxes.

Ultrasensitive Determination of Sugar Phosphates in Trace Samples by Stable Isotope Chemical Labeling Combined with RPLC-MS

Sugar phosphates are important metabolic intermediates in organisms and play a vital role in energy and central carbon metabolism. Profiling of sugar phosphates is of great significance but full of challenges due to their high structural similarity and low sensitivities in liquid chromatography (LC)-mass spectrometry (MS). In this study, we developed a novel stable isotope chemical labeling combined with the reversed-phase (RP)LC-MS method for ultrasensitive determination of sugar phosphates at the single-cell level. By chemical derivatization with 2-(diazo-methyl)-N-methyl-N-phenyl-benzamide (2-DMBA) and d₅-2-DMBA, sugar phosphate isomers can obtain better separation and identification, and the detection sensitivities of sugar phosphates increased by 3.5-147 folds. The obtained limits of detection of sugar phosphates ranged from 5 to 16 pg/mL. Using this method, we achieved ultrasensitive and accurate quantification of 12 sugar phosphates in different trace biological samples. Benefiting from the improved separation and detection sensitivity, we successfully quantified five sugar phosphates (d-glucose 1-phosphate, d-mannose 6-phosphate, d-fructose 6-phosphate, d-glucose 6-phosphate, and seduheptulose 7-phosphate) in a single protoplast of Arabidopsis thaliana.

mfapy: An open-source Python package for 13C-based metabolic flux analysis

¹³C-based metabolic flux analysis (¹³C-MFA) is an essential tool for estimating intracellular metabolic flux levels in metabolic engineering and biology. In ¹³C-MFA, a metabolic flux distribution that explains the observed isotope labeling data was computationally estimated using a non-linear optimization method. Herein, we report the development of mfapy, an open-source Python package developed for more flexibility and extensibility for ¹³C-MFA. mfapy compels users to write a customized Python code by describing each step in the data analysis procedures of the isotope labeling experiments. The flexibility and extensibility provided by mfapy can support trial-and-error performance in the routine estimation of metabolic flux distributions, experimental design by computer simulations of ¹³C-MFA experiments, and development of new data analysis techniques for stable isotope labeling experiments. mfapy is available to the public from the Github repository (https://github.com/fumiomatsuda/mfapy).

•

An open-source Python package, mfapy, is developed for ¹³C-MFA.

•

mfapy enables users to write Python codes for data analysis procedures of ¹³C-MFA.

•

mfapy has a flexibility and extensibility to support various data analysis procedures.

•

Computer simulations of ¹³C-MFA experiments is supported for experimental design.

Computational data mining method for isotopomer analysis in the quantitative assessment of metabolic reprogramming

Measurement of metabolic flux levels using stable isotope labeling has been successfully used to investigate metabolic redirection and reprogramming in living cells or tissues. The metabolic flux ratio between two reactions can be estimated from the ¹³C-labeling patterns of a few metabolites combined with the knowledge of atom mapping in the complicated metabolic network. However, it remains unclear whether an observed change in the labeling pattern of the metabolites is sufficient evidence of a shift in flux ratio between two metabolic states. In this study, a data analysis method was developed for the quantitative assessment of metabolic reprogramming. The Metropolis-Hastings algorithm was used with an in silico metabolic model to generate a probability distribution of metabolic flux levels under a condition in which the ¹³C-labeling pattern was observed. Reanalysis of literature data demonstrated that the developed method enables analysis of metabolic redirection using whole ¹³C-labeling pattern data. Quantitative assessment by Cohen’s effect size (d) enables a more detailed read-out of metabolic reprogramming information. The developed method will enable future applications of the metabolic isotopomer analysis to various targets, including cultured cells, whole tissues, and organs.

Two-step derivatization for determination of sugar phosphates in plants by combined reversed phase chromatography/tandem mass spectrometry

BACKGROUND

Sugar phosphates are important intermediates of central carbon metabolism in biological systems, with roles in glycolysis, the pentose-phosphate pathway, tricarboxylic acid (TCA) cycle, and many other biosynthesis pathways. Understanding central carbon metabolism requires a simple, robust and comprehensive analytical method. However, sugar phosphates are notoriously difficult to analyze by traditional reversed phase liquid chromatography.

RESULTS

Here, we show a two-step derivatization of sugar phosphates by methoxylamine and propionic acid anhydride after chloroform/methanol (3:7) extraction from Populus leaf and developing wood that improves separation, identification and quantification of sugar phosphates by ultra high performance liquid chromatography-electrospray ionization-mass spectrometry (UHPLC-ESI-MS). Standard curves of authentic sugar phosphates were generated for concentrations from pg to ng/μl with a correlation coefficient R ² > 0.99. The method showed high sensitivity and repeatability with relative standard deviation (RSD) < 20% based on repeated extraction, derivatization and detection. The analytical accuracy for Populus leaf extracts, determined by a two-level spiking approach of selected metabolites, was 79-107%.

CONCLUSION

The results show the reliability of combined reversed phase liquid chromatography-tandem mass spectrometry for sugar phosphate analysis and demonstrate the presence of two unknown sugar phosphates in Populus extracts.