Method selectivity evaluation using the co-feature ratio in LC/MS metabolomics: Comparison of HILIC stationary phase performance for the analysis of plasma, urine and cell extracts

Comparison of reversed-phase, hydrophilic interaction, and porous graphitic carbon chromatography columns for an untargeted toxicometabolomics study in pooled human liver microsomes, rat urine, and rat plasma

INTRODUCTION

Untargeted metabolomics studies are expected to cover a wide range of compound classes with high chemical diversity and complexity. Thus, optimizing (pre-)analytical parameters such as the analytical liquid chromatography (LC) column is crucial and the selection of the column depends primarily on the study purpose.

OBJECTIVES

The current investigation aimed to compare six different analytical columns. First, by comparing the chromatographic resolution of selected compounds. Second, on the outcome of an untargeted toxicometabolomics study using pooled human liver microsomes (pHLM), rat plasma, and rat urine as matrices.

METHODS

Separation and analysis were performed using three different reversed-phase (Phenyl-Hexyl, BEH C18, and Gold C18), two hydrophilic interaction chromatography (HILIC) (ammonium-sulfonic acid and sulfobetaine), and one porous graphitic carbon (PGC) columns coupled to high-resolution mass spectrometry (HRMS). Their impact was evaluated based on the column performance and the size of feature count, amongst others.

RESULTS

All three reversed-phase columns showed a similar performance, whereas the PGC column was superior to both HILIC columns at least for polar compounds. Comparing the size of feature count across all datasets, most features were detected using the Phenyl-Hexyl or sulfobetaine column. Considering the matrices, most significant features were detected in urine and pHLM after using the sulfobetaine and in plasma after using the ammonium-sulfonic acid column.

CONCLUSION

The results underline that the outcome of this untargeted toxicometabolomic study LC-HRMS metabolomic study was highly influenced by the analytical column, with the Phenyl-Hexyl or sulfobetaine column being the most suitable. However, column selection may also depend on the investigated compounds as well as on the investigated matrix.

Systematic Evaluation of HILIC Stationary Phases for Global Metabolomics of Human Plasma

Polar hydrophilic metabolites have been identified as important actors in many biochemical pathways. Despite continuous improvement and refinement of hydrophilic interaction liquid chromatography (HILIC) platforms, its application in global polar metabolomics has been underutilized. In this study, we aimed to systematically evaluate polar stationary phases for untargeted metabolomics by using HILIC columns (neutral and zwitterionic) that have been exploited widely in targeted approaches. To do so, high-resolution mass spectrometry was applied to thoroughly investigate selectivity, repeatability and matrix effect at three pH conditions for 9 classes of polar compounds using 54 authentic standards and plasma matrix. The column performance for utilization in untargeted metabolomics was assessed using plasma samples with diverse phenotypes. Our results indicate that the ZIC-c HILIC column operated at neutral pH exhibited several advantages, including superior performance for different classes of compounds, better isomer separation, repeatability and high metabolic coverage. Regardless of the column type, the retention of inorganic ions in plasma leads to extensive adduct formation and co-elution with analytes, which results in ion-suppression as part of the overall plasma matrix effect. In ZIC-c HILIC, the sodium chloride ion effect was particularly observed for amino acids and amine classes. Successful performance of HILIC for separation of plasma samples with different phenotypes highlights this mode of separation as a valuable approach in global profiling of plasma sample and discovering the metabolic changes associated with health and disease.

The Effects of Sampling and Storage Conditions on the Metabolite Profile of the Marine Sponge Geodia barretti

Geodia barretti is a deep-sea marine sponge common in the north Atlantic and waters outside of Norway and Sweden. The sampling and subsequent treatment as well as storage of sponges for metabolomics analyses can be performed in different ways, the most commonly used being freezing (directly upon collection or later) or by storage in solvent, commonly ethanol, followed by freeze-drying. In this study we therefore investigated different sampling protocols and their effects on the detected metabolite profiles in liquid chromatography-mass spectrometry (LC-MS) using an untargeted metabolomics approach. Sponges (G. barretti) were collected outside the Swedish west coast and pieces from three sponge specimens were either flash frozen in liquid nitrogen, frozen later after the collection cruise, stored in ethanol or stored in methanol. The storage solvents as well as the actual sponge pieces were analyzed, all samples were analyzed with hydrophilic interaction liquid chromatography as well as reversed phase liquid chromatography with high resolution mass spectrometry using full-scan in positive and negative ionization mode. The data were evaluated using multivariate data analysis. The highest metabolite intensities were found in the frozen samples (flash frozen and frozen after sampling cruise) as well as in the storage solvents (methanol and ethanol). Metabolites extracted from the sponge pieces that had been stored in solvent were found in very low intensity, since the majority of metabolites were extracted to the solvents to a high degree. The exception being larger peptides and some lipids. The lowest variation between replicates were found in the flash frozen samples. In conclusion, the preferred method for sampling of sponges for metabolomics was found to be immediate freezing in liquid nitrogen. However, freezing the sponge samples after some time proved to be a reliable method as well, albeit with higher variation between the replicates. The study highlights the importance of saving ethanol extracts after preservation of specimens for biology studies; these valuable extracts could be further used in studies of natural products, chemosystematics or metabolomics.

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.

High-Precision Automated Workflow for Urinary Untargeted Metabolomic Epidemiology

Urine is a noninvasive biofluid that is rich in polar metabolites and well suited for metabolomic epidemiology. However, because of individual variability in health and hydration status, the physiological concentration of urine can differ >15-fold, which can pose major challenges in untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics. Although numerous urine normalization methods have been implemented (e.g., creatinine, specific gravity-SG), most are manual and, therefore, not practical for population-based studies. To address this issue, we developed a method to measure SG in 96-well-plates using a refractive index detector (RID), which exhibited accuracy within 85-115% and <3.4% precision. Bland-Altman statistics showed a mean deviation of -0.0001 SG units (limits of agreement: -0.0014 to 0.0011) relative to a hand-held refractometer. Using this RID-based SG normalization, we developed an automated LC-MS workflow for untargeted urinary metabolomics in a 96-well-plate format. The workflow uses positive and negative ionization HILIC chromatography and acquires mass spectra in data-independent acquisition (DIA) mode at three collision energies. Five technical internal standards (tISs) were used to monitor data quality in each method, all of which demonstrated raw coefficients of variation (CVs) < 10% in the quality controls (QCs) and < 20% in the samples for a small cohort (n = 87 urine samples, n = 22 QCs). Application in a large cohort (n = 842 urine samples, n = 248 QCs) demonstrated CVQC < 5% and CVsamples < 16% for 4/5 tISs after signal drift correction by cubic spline regression. The workflow identified >540 urinary metabolites including endogenous and exogenous compounds. This platform is suitable for performing urinary untargeted metabolomic epidemiology and will be useful for applications in population-based molecular phenotyping.

Improved Sensitivity in Hydrophilic Interaction Liquid Chromatography-Electrospray-Mass Spectrometry after Removal of Sodium and Potassium Ions from Biological Samples

Inorganic ions, such as sodium and potassium, are present in all biological matrices and are sometimes also added during sample preparation. However, these inorganic ions are known to hamper electrospray ionization -mass spectrometry (ESI-MS) applications, especially in hydrophilic interaction liquid chromatography (HILIC) where they are retained and can be detected as adducts and clusters with mobile phase components or analytes. The retention of inorganic ions leads to co-elution with analytes and as a result ion-suppression, extensive adduct formation and problems with reproducibility. In the presented work, a sample preparation method using cation exchange solid phase extraction (SPE) was developed to trap Na⁺ and K⁺ ions from human blood plasma and head and neck cancer cells for the analysis of small cationic, anionic as well as neutral organic analytes. The investigated analytes were small, hydrophilic compounds typically in focus in metabolomics studies. The samples were analyzed using full-scan HILIC-ESI-quadrupole time of flight (QTOF)-MS with an untargeted, screening approach. Method performance was evaluated using multivariate data analysis as well as relative quantifications, spiking of standards to evaluate linearity of response and post-column infusion to study ion-suppression. In blood plasma, the reduction of sodium and potassium ion concentration resulted in improved sensitivity increased signal intensity for 19 out of 28 investigated analytes, improved linearity of response, reduced ion-suppression and reduced cluster formation as well as adduct formation. Thus, the presented method has significant potential to improve data quality in metabolomics studies.

Reviewing the metabolome coverage provided by LC-MS: Focus on sample preparation and chromatography-A tutorial

Metabolomics has become an invaluable tool for both studying metabolism and biomarker discovery. The great technical advances in analytical chemistry and bioinformatics have considerably increased the number of measurable metabolites, yet an important part of the human metabolome remains uncovered. Among the various MS hyphenated techniques available, LC-MS stands out as the most used. Here, we aimed to show the capabilities of LC-MS to uncover part of the metabolome and how to best proceed with sample preparation and LC to maximise metabolite detection. The analyses of various open metabolite databases served us to estimate the size of the already detected human metabolome, the expected metabolite composition of most used human biospecimens and which part of the metabolome can be detected when LC-MS is used. Based on an extensive review and on our experience, we have outlined standard procedures for LC-MS analysis of urine, cells, serum/plasma, tissues and faeces, to guide in the selection of the sample preparation method that best matches with one or more LC techniques in order to get the widest metabolome coverage. These standard procedures may be a useful tool to explore, at a glance, the wide spectrum of possibilities available, which can be a good starting point for most of the LC-MS metabolomic studies.

A Metabolomics Workflow for Analyzing Complex Biological Samples Using a Combined Method of Untargeted and Target-List Based Approaches

In the highly dynamic field of metabolomics, we have developed a method for the analysis of hydrophilic metabolites in various biological samples. Therefore, we used hydrophilic interaction chromatography (HILIC) for separation, combined with a high-resolution mass spectrometer (MS) with the aim of separating and analyzing a wide range of compounds. We used 41 reference standards with different chemical properties to develop an optimal chromatographic separation. MS analysis was performed with a set of pooled biological samples human cerebrospinal fluid (CSF), and human plasma. The raw data was processed in a first step with Compound Discoverer 3.1 (CD), a software tool for untargeted metabolomics with the aim to create a list of unknown compounds. In a second step, we combined the results obtained with our internally analyzed reference standard list to process the data along with the Lipid Data Analyzer 2.6 (LDA), a software tool for a targeted approach. In order to demonstrate the advantages of this combined target-list based and untargeted approach, we not only compared the relative standard deviation (%RSD) of the technical replicas of pooled plasma samples (n = 5) and pooled CSF samples (n = 3) with the results from CD, but also with XCMS Online, a well-known software tool for untargeted metabolomics studies. As a result of this study we could demonstrate with our HILIC-MS method that all standards could be either separated by chromatography, including isobaric leucine and isoleucine or with MS by different mass. We also showed that this combined approach benefits from improved precision compared to well-known metabolomics software tools such as CD and XCMS online. Within the pooled plasma samples processed by LDA 68% of the detected compounds had a %RSD of less than 25%, compared to CD and XCMS online (57% and 55%). The improvements of precision in the pooled CSF samples were even more pronounced, 83% had a %RSD of less than 25% compared to CD and XCMS online (28% and 8% compounds detected). Particularly for low concentration samples, this method showed a more precise peak area integration with its 3D algorithm and with the benefits of the LDAs graphical user interface for fast and easy manual curation of peak integration. The here-described method has the advantage that manual curation for larger batch measurements remains minimal due to the target list containing the information obtained by an untargeted approach.

Superhydrophilicity and strong salt-affinity: Zwitterionic polymer grafted surfaces with significant potentials particularly in biological systems

In recent years, zwitterionic polymers have been frequently reported to modify various surfaces to enhance hydrophilicity, antifouling and antibacterial properties, which show significant potentials particularly in biological systems. This review focuses on the fabrication, properties and various applications of zwitterionic polymer grafted surfaces. The "graft-from" and "graft-to" strategies, surface grafting copolymerization and post zwitterionization methods were adopted to graft lots type of the zwitterionic polymers on different inorganic/organic surfaces. The inherent hydrophilicity and salt affinity of the zwitterionic polymers endow the modified surfaces with antifouling, antibacterial and lubricating properties, thus the obtained zwitterionic surfaces show potential applications in biosystems. The zwitterionic polymer grafted membranes or stationary phases can effectively separate plasma, water/oil, ions, biomolecules and polar substrates. The nanomedicines with zwitterionic polymer shells have "stealth" effect in the delivery of encapsulated drugs, siRNA or therapeutic proteins. Moreover, the zwitterionic surfaces can be utilized as wound dressing, self-healing or oil extraction materials. The zwitterionic surfaces are expected as excellent support materials for biosensors, they are facing the severe challenges in the surface protection of marine facilities, and the dense ion pair layers may take unexpected role in shielding the grafted surfaces from strong electromagnetic field.

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.

Advances and challenges in development of precision psychiatry through clinical metabolomics on mood and psychotic disorders

Metabolomics is defined as the study of the global metabolite profile in a system under a given set of conditions. The objective of this review is to comprehensively assess the literature on metabolomics in mood disorders and schizophrenia and provide data for mental health researchers about the challenges and potentials of metabolomics. The majority of studies in metabolomics in Psychiatry uses peripheral blood or urine. The most widely used analytical techniques in metabolomics research are nuclear magnetic resonance (NMR) and mass spectrometry (MS). They are multiparametric and provide extensive structural and conformational information on multiple chemical classes. NMR is useful in untargeted analysis, which focuses on biosignatures or 'metabolic fingerprints' of illnesses. MS targeted metabolomics approach focuses on the identification and quantification of selected metabolites known to be involved in a particular metabolic pathway. The available studies of metabolomics in Schizophrenia, Bipolar Disorder and Major Depressive Disorder suggest a potential in investigating metabolic pathways involved in these diseases' pathophysiology and response to treatment, as well as its potential in biomarkers identification.

Adduct formation in electrospray ionisation-mass spectrometry with hydrophilic interaction liquid chromatography is strongly affected by the inorganic ion concentration of the samples

Hydrophilic interaction liquid chromatography (HILIC)/ electrospray ionisation-mass spectrometry (ESI-MS) has gained interest for the analysis of polar analytes in bioanalytical applications in recent years. However, ESI-MS is prone to adduct formation of analytes. In contrast to reversed phase chromatography, small inorganic ions have retention in HILIC, i.e. analytes and inorganic ions may co-elute, which could influence the adduct formation. In the present paper, it was demonstrated that the co-elution of sodium ions or potassium ions and analytes in HILIC/ESI-MS affect the adduct formation and that different concentrations of sodium ions and potassium ions in biological samples could have an impact on the quantitative response of the respective adducts as well as the quantitative response of the protonated adduct. The co-elution also lead to cluster formation of analytes and sodium formate or potassium formate, causing extremely complicated spectra. In analytical applications using HILIC/ESI-MS where internal standards are rarely used or not properly matched, great care needs to be taken to ensure minimal variation of inorganic ion concentration between samples. Moreover, the use of alkali metal ion adducts as quantitative target ions in relative quantitative applications should be made with caution if proper internal standards are not used.