Metabolomic analysis of mammalian cells and human tissue through one-pot two stage derivatizations using sheathless capillary electrophoresis-electrospray ionization-mass spectrometry

Metabolomics: A useful tool for ischemic stroke research

Ischemic stroke (IS) is a multifactorial and heterogeneous disease. Despite years of studies, effective strategies for the diagnosis, management and treatment of stroke are still lacking in clinical practice. Metabolomics is a growing field in systems biology. It is starting to show promise in the identification of biomarkers and in the use of pharmacometabolomics to help patients with certain disorders choose their course of treatment. The development of metabolomics has enabled further and more biological applications. Particularly, metabolomics is increasingly being used to diagnose diseases, discover new drug targets, elucidate mechanisms, and monitor therapeutic outcomes and its potential effect on precision medicine. In this review, we reviewed some recent advances in the study of metabolomics as well as how metabolomics might be used to identify novel biomarkers and understand the mechanisms of IS. Then, the use of metabolomics approaches to investigate the molecular processes and active ingredients of Chinese herbal formulations with anti-IS capabilities is summarized. We finally summarized recent developments in single cell metabolomics for exploring the metabolic profiles of single cells. Although the field is relatively young, the development of single cell metabolomics promises to provide a powerful tool for unraveling the pathogenesis of IS.

Use of N-(4-aminophenyl)piperidine derivatization to improve organic acid detection with supercritical fluid chromatography-mass spectrometry

The analysis of organic acids in complex mixtures by LC-MS can often prove challenging, especially due to the poor sensitivity of negative ionization mode required for detection of these compounds in their native (i.e., underivatized or untagged) form. These compounds have also been difficult to measure using supercritical fluid chromatography (SFC)-MS, a technique of growing importance for metabolomic analysis, with similar limitations based on negative ionization. In this report, the use of a high proton affinity N-(4-aminophenyl)piperidine derivatization tag is explored for the improvement of organic acid detection by SFC-MS. Four organic acids (lactic, succinic, malic, and citric acids) with varying numbers of carboxylate groups were derivatized with N-(4-aminophenyl)piperidine to achieve detection limits down to 0.5 ppb, with overall improvements in detection limit ranging from 25-to-2100-fold. The effect of the derivatization group on sensitivity, which increased by at least 200-fold for compounds that were detectable in their native form, and mass spectrometric detection are also described. Preliminary investigations into the separation of these derivatized compounds identified multiple stationary phases that could be used for complete separation of all four compounds by SFC. This derivatization technique provides an improved approach for the analysis of organic acids by SFC-MS, especially for those that are undetectable in their native form.

Chemical Derivatization to Enhance Capillary Electrophoresis Mass Spectrometric Analysis of Acidic Metabolites in Mammalian Cells

The simultaneous analysis of cationic and anionic metabolites using capillary electrophoresis-mass spectrometry (CE-MS) has been considered challenging, as often two different analytical methods are required. Although CE-MS methods for cationic metabolite profiling have already shown good performance metrics, the profiling of anionic metabolites often results in relatively low sensitivity and poor repeatability caused by problems related to unstable electrospray and corona discharge when using reversed CE polarity and detection by MS in negative ionization mode. In this protocol, we describe a chemical derivatization procedure that provides a permanent positive charge to acidic metabolites, thereby allowing us to profile anionic metabolites by CE-MS using exactly the same separation conditions as employed for the analysis of basic metabolites. The utility of the overall approach is demonstrated for the analysis of energy metabolism-related metabolites in low numbers of HepG2 cells.

Analysis of endogenous metabolites using multifunctional derivatization and capillary RPLC-MS

Heterogeneity in metabolite structure and charge state complicates their analysis in electrospray mass spectrometry (ESI-MS). Complications such as diminished signal response and quantitation can be reduced by sequential dual-stage derivatization and capillary RP LC-ESI-MS analysis. Our sequential dual-stage chemical derivatization reacts analyte primary amine and hydroxyl groups with a linear acyl chloride head containing a tertiary amine moiety. Analyte carboxylate groups are then coupled to a linear amine tag with a tertiary amine moiety. This increase in the number of tags on analytes increases analyte proton affinity and hydrophobicity. We derivatized 250 metabolite standards which on average improved signal to noise by >44-fold, with an average limit of detection of 66 nM and R² of 0.98. This system detected 107 metabolites from 18 BAECs, 111 metabolites from human urine, and 153 from human serum based on retention time, exact mass, and MS/MS matches from a derivatized standard library. As a proof of concept, aortic endothelial cells were treated with epinephrine and analyzed by the dual-stage derivatization. We observed changes in 32 metabolites with many increases related to energy metabolism, specifically in the TCA cycle. A decrease in lactate levels and corresponding increase in pyruvate levels suggest that epinephrine causes a movement away from glycolytic reliance on energy and a shift towards the more efficient TCA respiration for increasing energy.

Isobaric 4-Plex Tagging for Absolute Quantitation of Biological Acids in Diabetic Urine Using Capillary LC-MS/MS

Isobaric labeling in mass spectrometry enables multiplexed absolute quantitation and high throughput, while minimizing full scan spectral complexity. Here, we use 4-plex isobaric labeling with a fixed positive charge tag to improve quantitation and throughput for polar carboxylic acid metabolites. The isobaric tag uses an isotope-encoded neutral loss to create mass-dependent reporters spaced 2 Da apart and was validated for both single- and double-tagged analytes. Tags were synthesized in-house using deuterated formaldehyde and methyl iodide in a total of four steps, producing cost-effective multiplexing. No chromatographic deuterium shifts were observed for single- or double-tagged analytes, producing consistent reporter ratios across each peak. Perfluoropentanoic acid was added to the sample to drastically increase retention of double-tagged analytes on a C18 column. Excess tag was scavenged and extracted using hexadecyl chloroformate after reaction completion. This allowed for removal of excess tag that typically causes ion suppression and column overloading. A total of 54 organic acids were investigated, producing an average linearity of 0.993, retention time relative standard deviation (RSD) of 0.58%, and intensity RSD of 12.1%. This method was used for absolute quantitation of acid metabolites comparing control and type 1 diabetic urine. Absolute quantitation of organic acids was achieved by using one isobaric lane for standards, thereby allowing for analysis of six urine samples in two injections. Quantified acids showed good agreement with previous work, and six significant changes were found. Overall, this method demonstrated 4-plex absolute quantitation of acids in a complex biological sample.

Network pharmacology combined with metabolomics to study the mechanism of Shenyan Kangfu Tablets in the treatment of diabetic nephropathy

ETHNOPHARMACOLOGICAL RELEVANCE

Shenyan Kangfu Tablets (SYKFT) is a traditional prescription evolved from Shenqi Pills. It has been included in the Synopsis of the Golden Chamber for more than 2000 years. SYKFT was listed as a national Chinese medicine protected class by the China Food and Drug Administration. Diabetic nephropathy (DN) is one of the serious microvascular diseases caused by diabetes and is also one of the important factors leading to the death of patients. The pathogenesis of DN is diverse and complex, and there is no particularly effective drug treatment. There is clinical evidence that SYKFT has a good therapeutic effect on DN with no obvious adverse effects, but the mechanism of treatment is not clear.

AIM OF THE STUDY

In this study, network pharmacology was combined with metabolomics technology to explore the mechanism of SYKFT in the treatment of DN.

MATERIALS AND METHODS

First, the research team conducted a qualitative study of the chemical components contained in SYKFT, and carried out network pharmacology to search for potential targets based on the characterized chemical components. Second, we analysed the metabolic profile of db/db mouse urine based on UHPLC-QTOF-MS technology, and biomarkers were identified by multivariate statistical analysis. Then, we performed further pathway enrichment analysis. Finally, the results of metabolomics and network pharmacology were conjointly analysed.

RESULTS

Seventy-five chemical components of SYKFT were identified. According to the TCMSP database, the corresponding targets of the qualitatively identified components were searched, and a total of 36 potentially active components and 160 targets related to DN were obtained. A total of 38 biomarkers were found in metabolomics based on UHPLC-QTOF-MS technology. Biosynthesis of unsaturated fatty acids and starch and sucrose metabolism are the most related pathways, the former of which has been rarely reported concerning DN. Finally, the results of the joint analysis show that two targets, hexokinase 2 (HK2) and maltase glucoamylase (MGAM), are the overlapping targets. It means they are not only the related targets of pathways involved in potential biomarkers in metabolomics but also the intersection targets of diseases and drugs identified by network pharmacology.

CONCLUSIONS

The study reveals that the potential mechanism of SYKFT is most related to insulin resistance (IR) in the treatment of DN. It also proves that network pharmacology combined with metabolomics to find the mechanisms by which herbs treat complex diseases is a feasible tool.

Application of Proteomics and Metabonomics to Reveal the Molecular Basis of Atractylodis Macrocephalae Rhizome for Ameliorating Hypothyroidism Instead of Hyperthyroidism

As the treatments of diseases with Chinese herbs are holistic and characterized by multiple components, pathways, and targets, elucidating the efficacy of Chinese herbs in treating diseases, and their molecular basis, requires a comprehensive, network-based approach. In this study, we used a network pharmacology strategy, as well as in vivo proteomics and metabonomics, to reveal the molecular basis by which Atractylodis macrocephalae rhizome (AMR) ameliorates hypothyroidism. Eighteen main compounds from AMR and its fractions (volatile oil fraction, crude polysaccharides fraction, lactones fraction, oligosaccharide fraction, and atractyloside fraction) were identified by HPLC, and their targets were screened using the TCMSP database and Swiss Target Prediction. Disease targets were gathered from the TTD, CTD and TCMSP databases. Hub targets were screened by different plug-ins, such as Bisogene, Merge, and CytoNCA, in Cytoscape 3.7.1 software and analyzed for pathways by the DAVID database. Hypothyroidism and hyperthyroidism pharmacological models were established through systems pharmacology based on proteomic and metabolomic techniques. Finally, AMR and its fractions were able to ameliorate the hypothyroidism model to different degrees, whereas no significant improvements were noted in the hyperthyroidism model. The lactones fraction and the crude polysaccharides fraction were considered the most important components of AMR for ameliorating hypothyroidism. These amelioration effects were achieved through promoting substance and energy metabolism. In sum, the integrative approach used in this study demonstrates how network pharmacology, proteomics, and metabolomics can be used effectively to elucidate the efficacy, molecular basis, and mechanism of action of medicines used in TCM.

3D-Printed, Modular, and Parallelized Microfluidic System with Customizable Scaffold Integration to Investigate the Roles of Basement Membrane Topography on Endothelial Cells

Because dysfunctions of endothelial cells are involved in many pathologies, in vitro endothelial cell models for pathophysiological and pharmaceutical studies have been a valuable research tool. Although numerous microfluidic-based endothelial models have been reported, they had the cells cultured on a flat surface without considering the possible three-dimensional (3D) structure of the native extracellular matrix (ECM). Endothelial cells rest on the basement membrane in vivo, which contains an aligned microfibrous topography. To better understand and model the cells, it is necessary to know if and how the fibrous topography can affect endothelial functions. With conventional fully integrated microfluidic apparatus, it is difficult to include additional topographies in a microchannel. Therefore, we developed a modular microfluidic system by 3D-printing and electrospinning, which enabled easy integration and switching of desired ECM topographies. Also, with standardized designs, the system allowed for high flow rates up to 4000 μL/min, which encompassed the full shear stress range for endothelial studies. We found that the aligned fibrous topography on the ECM altered arginine metabolism in endothelial cells and thus increased nitric oxide production. There has not been an endothelial model like this, and the new knowledge generated thereby lays a groundwork for future endothelial research and modeling.

Normalization of Samples of Limited Amounts in Quantitative Metabolomics Using Liquid Chromatography Fluorescence Detection with Dansyl Labeling of Metabolites

Quantitative metabolomics requires the analysis of the same or a very similar amount of samples in order to accurately determine the concentration differences of individual metabolites in comparative samples. Ideally, the total amount or concentration of metabolites in each sample is measured to normalize all the analyzed samples. In this work, we describe a very sensitive method to measure a subclass of metabolites as a surrogate quantifier for normalization of samples with limited amounts. This method starts with low-volume dansyl labeling of all metabolites containing a primary/secondary amine or phenol group in a sample to produce a final solution of 21 μL. The dansyl-labeled metabolites generate fluorescence signals at 520 nm with photoexcitation at 250 nm. To remove the interference of dansyl hydroxyl products (Dns-OH) formed from the labeling reagents used, a fast-gradient liquid chromatography separation is used to elute Dns-OH using aqueous solution, followed by organic solvent elution to produce a chromatographic peak of labeled metabolites, giving a measurement throughput of 6 min per sample. The integrated fluorescence signals of the peak are found to be related to the injection amount of the dansyl-labeled metabolites. A calibration curve using mixtures of dansyl-labeled amino acids is used to determine the total concentration of labeled metabolites in a sample. This concentration is used for normalization of samples in the range from 2 to 120 μM in 21 μL with only 1 μL consumed for fluorescence quantification (i.e., 2-120 pmol). We demonstrate the application of this sensitive sample normalization method in comparative metabolome analysis of human cancer cells, MCF-7 cells, treated with and without resveratrol, using a starting material of as low as 500 cells.

Options of the Main Derivatization Approaches for Analytical ESI and MALDI Mass Spectrometry

The inclusion of preliminary chemical labeling (derivatization) in the analysis process by such powerful and widespread methods as electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) is a popular and widely used methodological approach. This is due to the need to remove some fundamental limitations inherent in these powerful analytic methods. Although a number of special reviews has been published discussing the utilization of derivatization approaches, the purpose of the present critical review is to comprehensively summarize, characterize and evaluate most of the previously developed and practically applied, as well as recently proposed representative derivatization reagents for ESI-MS and MALDI-MS platforms in their mostly sensitive positive ion mode and frequently hyphenated with separation techniques. The review is focused on the use of preliminary chemical labeling to facilitate the detection, identification, structure elucidation, quantification, profiling or MS imaging of compounds within complex matrices. Two main derivatization approaches, namely the introduction of permanent charge-fixed or highly proton affinitive residues into analytes are critically evaluated. In situ charge-generation, charge-switch and charge-transfer derivatizations are considered separately. The potential of using reactive matrices in MALDI-MS and chemical labeling in MS-based omics sciences is given.

CE-MS for metabolomics: Developments and applications in the period 2018-2020

Capillary electrophoresis-mass spectrometry (CE-MS) is now a mature analytical technique in metabolomics, notably for the efficient profiling of polar and charged metabolites. Over the past few years, (further) progress has been made in the design of improved interfacing techniques for coupling CE to MS; also, in the development of CE-MS approaches for profiling metabolites in volume-restricted samples, and in strategies that further enhance the metabolic coverage. In this article, which is a follow-up of a previous review article covering the years 2016-2018 (Electrophoresis 2019, 40, 165-179), the main (technological) developments in CE-MS methods and strategies for metabolomics are discussed covering the literature from July 2018 to June 2020. Representative examples highlight the utility of CE-MS in the fields of biomedical, clinical, microbial, plant and food metabolomics. A complete overview of recent CE-MS-based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, some general conclusions and perspectives are given.

Single cell metabolomics using mass spectrometry: Techniques and data analysis

Mass spectrometry (MS) based techniques are gaining popularity for metabolomics research due to their high sensitivity, wide detection range, and capability of molecular identification. Utilizing such powerful technique to explore the cellular metabolism at the single cell level not only appreciates the subtle cell-to-cell difference (i.e., cell heterogeneity), but also gains biological merits corresponding to individual cells or small cell subpopulations. In this review article, we first briefly summarize recent advances in single cell MS experimental techniques, and then emphasize on the single cell metabolomics data analysis approaches. Through implementation of statistical analysis and more advanced data analysis methods, single cell metabolomics is expected to find more potential applications in the translational and clinical fields in the future.

UHPLC-MS/MS profiling of histidine and bile acid metabolism in human gastric fluid for diagnosis of gastric diseases

Bile acids (BAs) are synthesized in the liver and can mediate homeostasis and various metabolism processes in the human body. Their levels in the gastrointestinal tract are closely related to various gastrointestinal diseases. In particular, farnesoid X receptor activated by free BAs is associated with overexpression of histidine decarboxylase in tumorigenesis. Therefore, comprehensive profiling of histamine (HIST), histidine (His), and BAs in biological samples can provide insight into the pathological mechanisms of gastrointestinal diseases. However, development of an analytical platform to profile HIST, His, and BAs in biological samples has several challenges such as highly different polarities between acidic and basic targets, low physiological concentrations of analytes, and high matrix interference of biological samples. In this study, an ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method combined with serial derivatization was developed to simultaneously determine HIST, His, and 5 BAs (cholic acid, deoxycholic acid, chenodeoxycholic acid, ursodeoxycholic acid, and lithocholic acid) in human gastric fluid. In serial derivatization, benzoyl chloride (BzCl) and N,N-dimethylethylenediamine (DMED) were used to selectively derivatize amino and carboxyl groups of analytes, respectively. After serial derivatization, all target derivatives were determined using a reverse-phase C18 LC column and positive multiple reaction monitoring (MRM) mode, with reasonable chromatographic separation and sensitive MS detection. To accurately quantify target metabolites, 7 stable isotope-labeled internal standards were used. The MS/MS spectra of DMED and Bz derivatives exhibited specific fragments via loss of a neutral molecule (dimethylamine; 45 Da) and inductive cleavage (benzoyl; m/z 105) from protonated molecules, enabling selection of appropriate MRM transition ions for selective and sensitive detection. The developed method was validated with respect to limits of detection and quantification, linearity, precision, accuracy, stability, and matrix effect. The established method was successfully applied to human gastric fluid samples. This method provides reliable quantification of HIST, His, and BAs in human gastric fluid and will be helpful to understand pathophysiological mechanisms of gastric diseases.

Microfibrous Extracellular Matrix Changes the Liver Hepatocyte Energy Metabolism via Integrins

Cell line-based liver models are critical tools for liver-related studies. However, the conventional monolayer culture of hepatocytes, the most widely used in vitro model, does not have the extracellular matrix (ECM), which contributes to the three-dimensional (3D) arrangement of the hepatocytes in the liver. As a result, the metabolic properties of the hepatocytes in the monolayer tissue culture may not accurately reflect those of the hepatocytes in the liver. Here, we developed a modular platform for 3D hepatocyte cultures on fibrous ECMs produced by electrospinning, a technique that can turn a polymer solution to the micro/nanofibers and has been widely used to produce scaffolds for 3D cell cultures. Metabolomics quantitation by liquid chromatography-mass spectrometry (LC-MS) indicated that Huh7 hepatocytes grown in microfibers electrospun from silk fibroin exhibited reduced glycolysis and tricarboxylic acid (TCA) cycle, as compared to the cells cultured as a monolayer. Further mechanistic studies suggested that integrins were correlated to the ECM's effects. This is the first time to report how an ECM scaffold could affect the fundamental metabolism of the hepatocytes via integrins.

Assessing the progression of gastric cancer via profiling of histamine, histidine, and bile acids in gastric juice using LC-MS/MS

Bile acid (BA) imbalance may be directly associated with gastric cancer and indirectly influence stomach carcinogenesis via overexpression of histidine decarboxylase (HDC), which converts histidine (His) into histamine (HIST). Moreover, the progression of gastric cancer, could change the gut microbiome, including bacteria spp. that produce secondary BAs. Gastric juice has various metabolites that could indicate gastric cancer-related stomach conditions. Therefore, profiling of HIST, His, and BAs in gastric juice is crucial for understanding the etiological mechanisms of gastric cancer. We used a profiling method to simultaneously determine targeted metabolites in gastric juice using liquid chromatography-tandem mass spectrometry (LC-MS/MS). We successfully analyzed 70 human gastric juice samples from patients with chronic superficial gastritis (CSG, n = 20), intestinal metaplasia (IM, n = 12), and gastric cancer (n = 38). Furthermore, we investigated the relevance between BA metabolism and gastric cancer. There were statistical differences in the metabolism of cholic acid (CA) into deoxycholic acid (DCA) based on the progression of CSG into IM and gastric cancer. Hence, the progression of gastric cancer might be related to the alterations in gut microbiome composition. We provide insight into the etiological mechanisms of the progression of gastric cancer and biomarkers to diagnose and treat gastric cancer.

Integrated strategy for accurately screening biomarkers based on metabolomics coupled with network pharmacology

Screening diagnostic biomarkers can be challenging due to the complexity of traditional Chinese medicine (TCM) and ambiguous pharmacological mechanisms. In this study, we reported an integrated strategy for accurately screening diagnostic biomarkers based on metabolomics coupled with network pharmacology. First, a feasible pharmacological model was established through systems pharmacology and based on metabolomics-based techniques to explore diagnostic biomarkers. While the components satisfying the q-value < 0.05, fold change (FC) ≥ 1.2 or FC ≤ 0.8, coefficient of variance (CV) ≤ 30%(QC) and the variable importance in the project (VIP) value > 1 are considered to be diagnostic biomarkers. Second, the ingredients were retained only when oral bioavailability (OB), Caco-2 permeability, drug half-life, TPSA and drug likeness (DL) satisfied the criteria (OB ≥ 40%; Caco-2 ≥ -0.4; HL ≥ 4 h; TPSA˂140; DL ≥ 0.18) suggested by the TCMSP database. Moreover, ingredients that exhibit extensive biological activity in TCM are also retained. Third, the effect targets of TCM were screened using the TCMSP database, Swiss Target Prediction and STICH online software. Disease targets were gathered from the therapeutic target database (TTD), PharmGkb and TCMSP database. Hub genes were screened by potential protein-protein interaction (PPI) network pharmacology analysis. Finally, a metabolic network pathway is established between the diagnostic biomarker and the hub gene. In the network analysis of metabolic pathways, most of the genes involved in this pathway are the second-step-obtained hub genes, which can explain the accuracy of the identified biomarkers. The proposed integrated strategy was successfully applied to explore the mechanism of action of Pulsatilla decoction (PD) in the treatment of acute ulcerative colitis (UC). Based on this integrated strategy, 23 potential biomarkers of acute UC treated with PD were identified. In conclusion, the integrated strategy provides novel insights into network pharmacology and metabolomics as effective tools to illuminate the mechanism of action of TCM.

Fragmentation of Multi-charged Derivatized Lysine Using Nanospray CID Tandem Mass Spectrometry

We demonstrate increasing the charge state of small molecules using derivatized lysine as our model system. Lysine is chemically tagged with three tertiary amines which enables efficient production of highly charged analytes. A +3 charge state is obtained from direct infusion nanoelectrospray conditions. Collisional activation of the +3 derivatized lysine yielded structurally informative product ions corresponding to cleavages across the analyte backbone and within the proton affinity tags. This suggests a role for multi-charging of metabolites in both targeted MRM analyses and untargeted analyses to help identify novel metabolites. Density functional calculations aid peak assignment and rationalization of structure-property relationships. Graphical Abstract.