HILIC-MS for metabolomics: An attractive and complementary approach to RPLC-MS

Large-scale, comprehensive plasma metabolomic analyses reveal potential biomarkers for the diagnosis of early-stage coronary atherosclerosis

BACKGROUND

Coronary atherosclerosis (CAS) is a prevalent and chronic life-threatening disease. However, the detection of CAS at an early stage is difficult because of the lack of effective noninvasive diagnostic methods. The present study aimed to characterize the plasma metabolome of early-stage CAS patients to discover metabolomic biomarkers, develop a novel metabolite-based model for accurate noninvasive diagnosis of early-stage CAS, and explore the underlying metabolic mechanisms involved.

METHODS

A total of 100 patients with early-stage CAS and 120 age- and sex-matched control subjects were recruited from the Chinese Han population and further randomly divided into training (n = 120) and test sets (n = 100). The metabolomic profiles of the plasma samples were analyzed by an integrated untargeted liquid chromatography-mass spectrometry approach, including two separation modes and two ionization modes. Univariate and multivariate statistical analyses were employed to identify potential biomarkers and construct an early-stage CAS diagnostic model.

RESULTS

The integrated analytical method established herein improved metabolite coverage compared with single chromatographic separation and MS ionization mode. A total of 80 metabolites were identified as potential biomarkers of early-stage CAS, and these metabolites were mainly involved in glycerophospholipid, fatty acid, sphingolipid, and amino acid metabolism. An effective diagnostic model for early-stage CAS was established, incorporating 11 metabolites and achieving areas under the receiver operating characteristic curve (AUCs) of 0.984 and 0.908 in the training and test sets, respectively.

CONCLUSIONS

Our study not only successfully developed an effective noninvasive diagnostic model for identifying early-stage CAS but also provided novel insights into the pathogenesis of CAS.

Development of a Global Metabo-Lipid-Prote-omics Workflow to Compare Healthy Proximal and Distal Colonic Epithelium in Mice

A multimetabo-lipid-prote-omics workflow was developed to characterize the molecular interplay within proximal (PC) and distal (DC) colonic epithelium of healthy mice. This multiomics data set lays the foundation to better understand the two tissue types and can be used to study, for example, colon-related diseases like colorectal cancer or inflammatory bowel disease. First, the methyl tert-butyl ether extraction method was optimized, so that from a single tissue biopsy >350 reference-matched metabolites, >1850 reference-matched lipids, and >4500 proteins were detected by using targeted and untargeted metabolomics, untargeted lipidomics, and proteomics. Next, each omics-data set was analyzed individually and then merged with the additional omics disciplines to generate a deep understanding of the underlying complex regulatory network within the colon. Our data demonstrates, for example, differences in mucin formation, detected on substrate level as well as on enzyme level, and altered lipid metabolism by the detection of phospholipases hydrolyzing sphingomyelins to ceramides. In conclusion, the combination of the three mass spectrometry-based omics techniques can better entangle the functional and regional differences between PC and DC tissue compared to each single omics technique.

Preparation and chromatographic evaluation of 9-oxa-10-phosphophenanthrene 10-oxide bonded phenyl stationary phase and investigation of its retention mechanism through nuclear magnetic resonance spectroscopy

BACKGROUND

In reversed-phase liquid chromatography, the C18 alkyl bonded phase, as the primary stationary phase, is widely used in pharmaceutical and food analysis. The phenyl bonded phase often serves as a complementary choice to the C18 phase to enhance the separation performance of specific categories of compounds. However, both C18 and the currently available phenyl bonded phase chromatography columns show room for further optimization in improving the separation efficiency of specific compound classes, such as dihydroflavonoids. Additionally, the potential role and impact of introducing phosphorus groups into chromatographic stationary phases have not been fully explored, indicating a promising direction for research.

RESULTS

In the present work, we prepared a novel phenyl stationary phase by bonding 9-oxa-10-phosphaphenanthrene 10-oxide onto silica gel. The obtained material was characterized by scanning electron microscopy, fourier transforms infrared spectroscopy, and elemental analysis. The results show that 9-oxa-10-phosphaphenanthrene 10-oxide was successfully bonded on the silica surface with a load of 3.90 %. Further chromatographic characterization in high-performance liquid chromatography exhibited high column efficiency (40,792 plates m-1 for the determination of biphenyl) and good stability (RSD of 0.28 %∼5.38 %). Moreover, we made a detailed study of the column separation mechanism by nuclear magnetic resonance spectroscopy titration experiment. Comparing to commercial phenyl column, the proposed stationary phase showed shorter retention time and higher throughput. In addition, the stationary phase has a strong ability to separate multiple types of compounds, which provides a new strategy for the separation of complex samples, such as active ingredients in traditional Chinese medicine.

SIGNIFICANCE

We have developed a novel phenyl column and conducted a comprehensive examination of its chromatographic performance, demonstrating excellent separation capabilities and high efficiency for both nonpolar and moderately polar aromatic compounds. Additionally, we explored the impact of phosphorus-containing groups on the separation performance of chromatographic stationary phases.

Quantification of amino acids secreted by yeast cells by hydrophilic interaction liquid chromatography-tandem mass spectrometry

Monitoring the levels of amino acids (AAs) in biological cell cultures provides key information to understand the regulation of cell growth and metabolism. Saccharomyces cerevisiae can naturally excrete AAs, making accurate detection and determination of amino acid levels within the cultivation medium pivotal for gaining insights into this still poorly known process. Given that most AAs lack ultraviolet (UV) chromophores or fluorophores necessary for UV and fluorescence detection, derivatization is commonly utilized to enhance amino acid detectability via UV absorption. Unfortunately, this can lead to drawbacks such as derivative instability, labor intensiveness, and poor reproducibility. Hence, this study aimed to develop an accurate and stable hydrophilic interaction liquid chromatography-tandem mass spectrometry analytical method for the separation of all 20 AAs within a short 17-min run time. The method provides satisfactory linearity and sensitivity for all analytes. The method has been validated for intra- and inter-day precision, accuracy, recovery, matrix effect, and stability. It has been successfully applied to quantify 20 AAs in samples of yeast cultivation medium. This endeavor seeks to enhance our comprehension of amino acid profiles in the context of cell growth and metabolism within yeast cultivation media.

A Look into Ocular Diseases: The Pivotal Role of Omics Sciences in Ophthalmology Research

Precision medicine is a new medical approach which considers both population characteristics and individual variability to provide customized healthcare. The transition from traditional reactive medicine to personalized medicine is based on a biomarker-driven process and a deep knowledge of biological mechanisms according to which the development of diseases occurs. In this context, the advancements in high-throughput omics technologies represent a unique opportunity to discover novel biomarkers and to provide an unbiased picture of the biological system. One of the medical fields in which omics science has started to be recently applied is that of ophthalmology. Ocular diseases are very common, and some of them could be highly disabling, thus leading to vision loss and blindness. The pathogenic mechanism of most ocular diseases may be dependent on various genetic and environmental factors, whose effect has not been yet completely understood. In this context, large-scale omics approaches are fundamental to have a comprehensive evaluation of the whole system and represent an essential tool for the development of novel therapies. This Review summarizes the recent advancements in omics science applied to ophthalmology in the last ten years, in particular by focusing on proteomics, metabolomics and lipidomics applications from an analytical perspective. The role of high-efficiency separation techniques coupled to (high-resolution) mass spectrometry ((HR)MS) is also discussed, as well as the impact of sampling, sample preparation and data analysis as integrating parts of the analytical workflow.

Lipidomics reveals the reshaping of the mitochondrial phospholipid profile in cells lacking OPA1 and mitofusins

Depletion or mutations of key proteins for mitochondrial fusion, like optic atrophy 1 (OPA1) and mitofusins 1 and 2 (Mfn 1 and 2), are known to significantly impact the mitochondrial ultrastructure, suggesting alterations of their membranes' lipid profiles. In order to make an insight into this issue, we used hydrophilic interaction liquid chromatography coupled with electrospray ionization-high resolution MS to investigate the mitochondrial phospholipid (PL) profile of mouse embryonic fibroblasts knocked out for OPA1 and Mfn1/2 genes. One hundred sixty-seven different sum compositions were recognized for the four major PL classes of mitochondria, namely phosphatidylcholines (PCs, 63), phosphatidylethanolamines (55), phosphatidylinositols (21), and cardiolipins (28). A slight decrease in the cardiolipin/PC ratio was found for Mfn1/2-knockout mitochondria. Principal component analysis and hierarchical cluster analysis were subsequently used to further process hydrophilic interaction liquid chromatography-ESI-MS data. A progressive decrease in the incidence of alk(en)yl/acyl species in PC and phosphatidylethanolamine classes and a general increase in the incidence of unsaturated acyl chains across all the investigated PL classes was inferred in OPA1 and Mfn1/2 knockouts compared to WT mouse embryonic fibroblasts. These findings suggest a reshaping of the PL profile consistent with the changes observed in the mitochondrial ultrastructure when fusion proteins are absent. Based on the existing knowledge on the metabolism of mitochondrial phospholipids, we propose that fusion proteins, especially Mfns, might influence the PL transfer between the mitochondria and the endoplasmic reticulum, likely in the context of mitochondria-associated membranes.

Application of the Hydrophilic Interaction Liquid Chromatography (HILIC-MS) Novel Protocol to Study the Metabolic Heterogeneity of Glioblastoma Cells

Glioblastoma is a highly malignant brain tumor consisting of a heterogeneous cellular population. The transformed metabolism of glioblastoma cells supports their growth and division on the background of their milieu. One might hypothesize that the transformed metabolism of a primary glioblastoma could be well adapted to limitations in the variety and number of substrates imported into the brain parenchyma and present it their microenvironment. Additionally, the phenotypic heterogeneity of cancer cells could promote the variations among their metabolic capabilities regarding the utilization of available substrates and release of metabolic intermediates. With the aim to identify the putative metabolic footprint of different types of glioblastoma cells, we exploited the possibility for separation of polar and ionic molecules present in culture media or cell lysates by hydrophilic interaction liquid chromatography (HILIC). The mass spectrometry (MS) was then used to identify and quantify the eluted compounds. The introduced method allows the detection and quantification of more than 150 polar and ionic metabolites in a single run, which may be present either in culture media or cell lysates and provide data for polaromic studies within metabolomics. The method was applied to analyze the culture media and cell lysates derived from two types of glioblastoma cells, T98G and U118. The analysis revealed that even both types of glioblastoma cells share several common metabolic aspects, and they also exhibit differences in their metabolic capability. This finding agrees with the hypothesis about metabolic heterogeneity of glioblastoma cells. Furthermore, the combination of both analytical methods, HILIC-MS, provides a valuable tool for metabolomic studies based on the simultaneous identification and quantification of a wide range of polar and ionic metabolites-polaromics.

Applications of chromatographic methods in metabolomics: A review

Chromatography is a robust and reliable separation method that can use various stationary phases to separate complex mixtures commonly seen in metabolomics. This review examines the types of chromatography and stationary phases that have been used in targeted or untargeted metabolomics with methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. General considerations for sample pretreatment and separations in metabolomics are considered, along with the various supports and separation formats for chromatography that have been used in such work. The types of liquid chromatography (LC) that have been most extensively used in metabolomics will be examined, such as reversed-phase liquid chromatography and hydrophilic liquid interaction chromatography. In addition, other forms of LC that have been used in more limited applications for metabolomics (e.g., ion-exchange, size-exclusion, and affinity methods) will be discussed to illustrate how these techniques may be utilized for new and future research in this field. Multidimensional LC methods are also discussed, as well as the use of gas chromatography and supercritical fluid chromatography in metabolomics. In addition, the roles of chromatography in NMR- vs. MS-based metabolomics are considered. Applications are given within the field of metabolomics for each type of chromatography, along with potential advantages or limitations of these separation methods.

Comparison of Three Widely Employed Extraction Methods for Metabolomic Analysis of Trypanosoma brucei

Trypanosoma brucei (Tb) is the causative agent of human African trypanosomiasis (HAT), also known as sleeping sickness, which can be fatal if left untreated. An understanding of the parasite's cellular metabolism is vital for the discovery of new antitrypanosomal drugs and for disease eradication. Metabolomics can be used to analyze numerous metabolic pathways described as essential to Tb. brucei but has some limitations linked to the metabolites' physicochemical properties and the extraction process. To develop an optimized method for extracting and analyzing Tb. brucei metabolites, we tested the three most commonly used extraction methods, analyzed the extracts by hydrophilic interaction liquid chromatography high-resolution mass spectrometry (HILIC LC-HRMS), and further evaluated the results using quantitative criteria including the number, intensity, reproducibility, and variability of features, as well as qualitative criteria such as the specific coverage of relevant metabolites. Here, we present the resulting protocols for untargeted metabolomic analysis of Tb. brucei using (HILIC LC-HRMS). © 2024 Wiley Periodicals LLC. Basic Protocol 1: Culture of Trypanosoma brucei brucei parasites Basic Protocol 2: Preparation of samples for metabolomic analysis of Trypanosoma brucei brucei Basic Protocol 3: LC-HRMS-based metabolomic data analysis of Trypanosoma brucei brucei.

Electrostatic Repulsion Hydrophilic Interaction Liquid Chromatography (ERLIC) for the Quantitative Analysis of Polyamines

Highly polar low molecular weight organic molecules are still very challenging to analyze by liquid chromatography. Yet, with the steadily increasing application of metabolomics and similar approaches in chemical analysis, separating polar compounds might be even more important. However, almost all established liquid chromatography techniques (i.e., normal and reversed phase, hydrophilic interaction liquid chromatography (HILIC), ion chromatography) struggle with either carry-over, low sensitivity, or a lack of retention. For improving these shortcomings, electrostatic repulsion hydrophilic interaction chromatography (ERLIC) might be an alternative. By combining a HILIC mobile phase, that is highly organic with a low water content, and an ion exchange column, a distinct layer system develops. When the analyte's charge is of the same direction as the stationary phase, retention and elution are determined by two antagonistic forces: electrostatic repulsion and hydrophilicity. One prominent group of challenging polar analytes are the polyamines cadaverine, putrescine, spermidine, and spermine. Carrying charges from +2 to +4 at physiological pH, these compounds are essential cell constituents and found in all living organisms. However, they are still notoriously challenging to analyze via the established liquid chromatography methods. In the present work, an ERLIC tandem mass spectrometry method has been exemplarily developed, optimized, and validated for the quantitative determination of cadaverine, putrescine, spermidine, and spermine. This method enables symmetrical peak shapes and good separation of analytes with different charges while simultaneously selectively detecting the co-eluting diamines by MS/MS. Furthermore, high linearity (R > 0.998) and sensitivity (LODs ≤ 2 ng/mL) have been proven. Thus, ERLIC may be interesting for both targeted and untargeted analysis approaches of highly charged low molecular weight organic molecules.

Electron-activated dissociation (EAD) for the complementary annotation of metabolites and lipids through data-dependent acquisition analysis and feature-based molecular networking, applied to the sentinel amphipod Gammarus fossarum

The past decades have marked the rise of metabolomics and lipidomics as the -omics sciences which reflect the most phenotypes in living systems. Mass spectrometry-based approaches are acknowledged for both quantification and identification of molecular signatures, the latter relying primarily on fragmentation spectra interpretation. However, the high structural diversity of biological small molecules poses a considerable challenge in compound annotation. Feature-based molecular networking (FBMN) combined with database searches currently sets the gold standard for annotation of large datasets. Nevertheless, FBMN is usually based on collision-induced dissociation (CID) data, which may lead to unsatisfying information. The use of alternative fragmentation methods, such as electron-activated dissociation (EAD), is undergoing a re-evaluation for the annotation of small molecules, as it gives access to additional fragmentation routes. In this study, we apply the performances of data-dependent acquisition mass spectrometry (DDA-MS) under CID and EAD fragmentation along with FBMN construction, to perform extensive compound annotation in the crude extracts of the freshwater sentinel organism Gammarus fossarum. We discuss the analytical aspects of the use of the two fragmentation modes, perform a general comparison of the information delivered, and compare the CID and EAD fragmentation pathways for specific classes of compounds, including previously unstudied species. In addition, we discuss the potential use of FBMN constructed with EAD fragmentation spectra to improve lipid annotation, compared to the classic CID-based networks. Our approach has enabled higher confidence annotations and finer structure characterization of 823 features, including both metabolites and lipids detected in G. fossarum extracts.

HILIC-IM-MS for Simultaneous Lipid and Metabolite Profiling of Bacteria

Although MALDI-ToF platforms for microbial identifications have found great success in clinical microbiology, the sole use of protein fingerprints for the discrimination of closely related species, strain-level identifications, and detection of antimicrobial resistance remains a challenge for the technology. Several alternative mass spectrometry-based methods have been proposed to address the shortcomings of the protein-centric approach, including MALDI-ToF methods for fatty acid/lipid profiling and LC-MS profiling of metabolites. However, the molecular diversity of microbial pathogens suggests that no single "ome" will be sufficient for the accurate and sensitive identification of strain- and susceptibility-level profiling of bacteria. Here, we describe the development of an alternative approach to microorganism profiling that relies upon both metabolites and lipids rather than a single class of biomolecule. Single-phase extractions based on butanol, acetonitrile, and water (the BAW method) were evaluated for the recovery of lipids and metabolites from Gram-positive and -negative microorganisms. We found that BAW extraction solutions containing 45% butanol provided optimal recovery of both molecular classes in a single extraction. The single-phase extraction method was coupled to hydrophilic interaction liquid chromatography (HILIC) and ion mobility-mass spectrometry (IM-MS) to resolve similar-mass metabolites and lipids in three dimensions and provide multiple points of evidence for feature annotation in the absence of tandem mass spectrometry. We demonstrate that the combined use of metabolites and lipids can be used to differentiate microorganisms to the species- and strain-level for four of the ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Acinetobacter baumannii, and Pseudomonas aeruginosa) using data from a single ionization mode. These results present promising, early stage evidence for the use of multiomic signatures for the identification of microorganisms by liquid chromatography, ion mobility, and mass spectrometry that, upon further development, may improve upon the level of identification provided by current methods.

Development of a Cation Exchange SPE-HILIC-MS/MS Method for the Determination of Ningnanmycin Residues in Tea and Chrysanthemum

Ningnanmycin is a widely used antibiotic in agricultural production that effectively controls fungal and viral diseases in tea trees and chrysanthemums. The polarity characteristic of ningnanmycin has posed limitations on the development of robust detection methods, thereby hindering effective monitoring and control measures. By combining cation exchange solid phase extraction (SPE) with hydrophilic interaction chromatography tandem mass spectrometry (HILIC-MS/MS), we have effectively tackled the issue pertaining to the separation and retention of ningnanmycin. The average recoveries of ningnanmycin in green tea, black tea, and chrysanthemum were 77.3-82.0%, 80.1-81.5%, and 74.0-80.0%, respectively. The intraday and interday relative standard deviations (RSDs) were below and equal to 7.7%. Good linearity was observed in the concentration range of 1-1000 μg/L (R2 > 0.998). The limits of detection (LODs) ranged from 1.1 μg/kg to 7.1 μg/kg, and the limits of quantification (LOQs) ranged from 3.6 μg/kg to 23.7 μg/kg for ningnanmycin. These results indicate the good accuracy, repeatability, reproducibility, and sensitivity of the method. It is suitable for detecting ningnanmycin in tea and chrysanthemum.

Comparison of Amine-Modified Polymeric Stationary Phases for Polar Metabolomic Analysis Based on Unified-Hydrophilic Interaction/Anion Exchange Liquid Chromatography/High-Resolution Mass Spectrometry (Unified-HILIC/AEX/HRMS)

In metabolomic analysis, one of the most commonly used techniques to support the detection sensitivity and quantitation of mass spectrometry is combining it with liquid chromatography. Recently, we developed a method that enables comprehensive single-run measurement of hydrophilic metabolites using unified-hydrophilic interaction/anion exchange liquid chromatography/high-resolution mass spectrometry (unified-HILIC/AEX/HRMS) with a polymer-based mixed amines column (Gelpack GL-HilicAex). However, the importance of stationary phase functional groups and mobile phase conditions for the separation mechanisms and sensitive detection in unified-HILIC/AEX/HRMS is not yet fully understood. This study aimed to understand the importance of the mobile and stationary phases in unified-HILIC/AEX/HRMS. Two different alkali-resistant polymer-based amines-modified columns (Gelpack GL-HilicAex, primary, secondary, tertiary, and quaternary amine-modified polyglycerol dimethacrylate gel; Asahipak NH2P-50 2D, secondary amine-modified polyvinyl alcohol gel) and two eluents (acetonitrile and ammonium bicarbonate solution, pH 9.8) were used for comparative validation. A comparison of mobile phase conditions using both columns confirmed that the two-step separation from HILIC to AEX characteristic of unified-HILIC/AEX requires a linear gradient condition from acetonitrile to nearly 50% water and AEX with up to 40 mM bicarbonate ions. We found that when alkali-resistant hydrophilic polymer packing materials are modified with amines, unified-HILIC/AEX separation can be reproduced if at least one secondary amine associated with the amine series is present in the stationary phase. Furthermore, the difference in sensitivity in the HILIC and AEX modes owing to the different columns indicates the need for further improvements in the mobile phase composition and stationary phase.

Global LC-MS/MS targeted metabolomics using a combination of HILIC and RP LC separation modes on an organic monolithic column based on 1-vinyl-1,2,4-triazole

The paper presents an LC-MS/MS-based approach to targeted screening of both polar and non-polar metabolites using a synthesized monolithic column which is a copolymer of styrene, divinylbenzene, and 1-vinyl-1,2,4-triazole. It was shown that this column in combination with eluents 20 mM (NH4)2CO3 + NH3 (pH = 9.8, eluent A) and ACN (eluent B) allows for separation of metabolites of different nature in two modes, HILIC and RP LC, and these methods are mutually complementary. A combination of analyses based on these two modes was proposed, allowing detection of about 400 metabolites in a total time of less than 30 min. Comparison of the developed method with those utilizing commercially available columns with sorbents of various types showed that it could provide a broader metabolite coverage. Using the developed approach, metabolomic screening of dried blood spots samples of mice exposed with X-ray was performed, and metabolites that could be considered as possible markers of irradiation exposure and organ tissue damage were detected. Analysis of marker metabolites revealed metabolic pathways that were altered by radiation exposure. Comparison of the results with literature data showed the effectiveness of the developed metabolomic screening approach.

Metabolomic evolution of the postpartum dairy cow uterus

High rates of early pregnancy loss are a critical issue in dairy herds, particularly in seasonal, grazing systems. Components of the uterine luminal fluid (ULF), on which the early embryo depends for sustenance and growth, partly determine early pregnancy losses. Here, changes in ULF from early to mid-postpartum in crossbred dairy cows were explored, linking them with divergent embryo development. For this, the uteri of 87 cows at Day 7 of pregnancy at first and third estrus postpartum were flushed to collect ULF. Eighteen metabolites (chiefly organic acids and sugars) significantly varied in abundance across postpartum, indicating a molecular signature of physiological recovery consistent of the upregulation of pyrimidine metabolism and glycerophospholipid metabolism, and downregulation of pentose phosphate and taurine metabolism pathways. Joint pathway analysis of metabolomics data and a previously generated proteomics data set on the same ULF samples suggests key links between postpartum recovery and subsequent successful embryo development. These include upregulation of VEGFA and downregulation of metabolism, NRF2, T-cell receptor, which appear to improve the ULF's capacity of sustaining normal embryo development, and a putative osmo-protectant role of beta-alanine. These relationships should be further investigated to develop tools to detect and reduce early pregnancy loss in dairy cows.

Opportunities and challenges for sample preparation and enrichment in mass spectrometry for single-cell metabolomics

Single-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the status quo in the cell, studying the metabolome at single-cell resolution may unravel said heterogeneity. A challenge in single-cell metabolome analysis is that metabolites cannot be amplified, so one needs to deal with picolitre volumes and a wide range of analyte concentrations. Due to high sensitivity and resolution, MS is preferred in single-cell metabolomics. Large numbers of cells need to be analysed for proper statistics; this requires high-throughput analysis, and hence automation of the analytical workflow. Significant advances in (micro)sampling methods, CE and ion mobility spectrometry have been made, some of which have been applied in high-throughput analyses. Microfluidics has enabled an automation of cell picking and metabolite extraction; image recognition has enabled automated cell identification. Many techniques have been used for data analysis, varying from conventional techniques to novel combinations of advanced chemometric approaches. Steps have been set in making data more findable, accessible, interoperable and reusable, but significant opportunities for improvement remain. Herein, advances in single-cell analysis workflows and data analysis are discussed, and recommendations are made based on the experimental goal.

Exploring Human Metabolome after Wine Intake-A Review

Wine has a rich history dating back to 2200 BC, originally recognized for its medicinal properties. Today, with the aid of advanced technologies like metabolomics and sophisticated analytical techniques, we have gained remarkable insights into the molecular-level changes induced by wine consumption in the human organism. This review embarks on a comprehensive exploration of the alterations in human metabolome associated with wine consumption. A great number of 51 studies from the last 25 years were reviewed; these studies systematically investigated shifts in metabolic profiles within blood, urine, and feces samples, encompassing both short-term and long-term studies of the consumption of wine and wine derivatives. Significant metabolic alterations were observed in a wide variety of metabolites belonging to different compound classes, such as phenolic compounds, lipids, organic acids, and amino acids, among others. Within these classes, both endogenous metabolites as well as diet-related metabolites that exhibited up-regulation or down-regulation following wine consumption were included. The up-regulation of short-chain fatty acids and the down-regulation of sphingomyelins after wine intake, as well as the up-regulation of gut microbial fermentation metabolites like vanillic and syringic acid are some of the most important findings reported in the reviewed literature. Our results confirm the intact passage of certain wine compounds, such as tartaric acid and other wine acids, to the human organism. In an era where the health effects of wine consumption are of growing interest, this review offers a holistic perspective on the metabolic underpinnings of this centuries-old tradition.

Unlocking the Hidden Depths: Multi-Modal Integration of Imaging Mass Spectrometry-Based and Molecular Imaging Techniques

Multimodal imaging (MMI) has emerged as a powerful tool in clinical research, combining different imaging modes to acquire comprehensive information and enabling scientists and surgeons to study tissue identification, localization, metabolic activity, and molecular discovery, thus aiding in disease progression analysis. While multimodal instruments are gaining popularity, challenges such as non-standardized characteristics, custom software, inadequate commercial support, and integration issues with other instruments need to be addressed. The field of multimodal imaging or multiplexed imaging allows for simultaneous signal reproduction from multiple imaging strategies. Intraoperatively, MMI can be integrated into frameless stereotactic surgery. Recent developments in medical imaging modalities such as magnetic resonance imaging (MRI), and Positron Emission Topography (PET) have brought new perspectives to multimodal imaging, enabling early cancer detection, molecular tracking, and real-time progression monitoring. Despite the evidence supporting the role of MMI in surgical decision-making, there is a need for comprehensive studies to validate and perform integration at the intersection of multiple imaging technologies. They were integrating mass spectrometry-based technologies (e.g., imaging mass spectrometry (IMS), imaging mass cytometry (IMC), and Ion mobility mass spectrometry ((IM-IM) with medical imaging modalities, offering promising avenues for molecular discovery and clinical applications. This review emphasizes the potential of multi-omics approaches in tissue mapping using MMI integrated into desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI), allowing for sequential analyses of the same section. By addressing existing knowledge gaps, this review encourages future research endeavors toward multi-omics approaches, providing a roadmap for future research and enhancing the value of MMI in molecular pathology for diagnosis.

Metabolic Basis of Circadian Dysfunction in Parkinson's Disease

Parkinson's disease (PD) is one of the most common neurodegenerative disorders. The management of PD is a challenging aspect for general physicians and neurologists. It is characterized by the progressive loss of dopaminergic neurons. Impaired α-synuclein secretion and dopamine release may cause mitochondrial dysfunction and perturb energy metabolism, subsequently altering the activity and survival of dopaminergic neurons, thus perpetuating the neurodegenerative process in PD. While the etiology of PD remains multifactorial, emerging research indicates a crucial role of circadian dysfunction in its pathogenesis. Researchers have revealed that circadian dysfunction and sleep disorders are common among PD subjects and disruption of circadian rhythms can increase the risk of PD. Hence, understanding the findings of circadian biology from translational research in PD is important for reducing the risk of neurodegeneration and for improving the quality of life. In this review, we discuss the intricate relationship between circadian dysfunction in cellular metabolism and PD by summarizing the evidence from animal models and human studies. Understanding the metabolic basis of circadian dysfunction in PD may shed light on novel therapeutic approaches to restore circadian rhythm, preserve dopaminergic function, and ameliorate disease progression. Further investigation into the complex interplay between circadian rhythm and PD pathogenesis is essential for the development of targeted therapies and interventions to alleviate the burden of this debilitating neurodegenerative disorder.

A liquid chromatography-tandem mass spectrometry based method for the quantification of adenosine nucleotides and NAD precursors and products in various biological samples

Adenine nucleotides (AN) are ubiquitous metabolites that regulate cellular energy metabolism and modulate cell communication and inflammation. To understand how disturbances in AN balance arise and affect cellular function, robust quantification techniques for these metabolites are crucial. However, due to their hydrophilicity, simultaneous quantification of AN across various biological samples has been challenging. Here we present a hydrophilic interaction high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) based method for the quantification of 26 adenosine nucleotides and precursors as well as metabolic products of nicotinamide adenine dinucleotide (NAD) in plasma, liver, and adipose tissue samples as well as cell culture supernatants and cells. Method validation was performed with regard to linearity, accuracy, precision, matrix effects, and carryover. Finally, analysis of cell culture supernatants derived from intestinal organoids and RAW 264.7 cells illustrates that the here described method is a reliable and easy-to-use tool to quantify AN and opens up new avenues to understand the role of AN generation and breakdown for cellular functions.

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.

Determination of underivatized amino acids in human plasma using ion pair liquid chromatography/tandem mass spectrometry

Accurate quantification of amino acids (AA) is essential for several applications, including clinical research, food analysis, and pharmaceutical studies. In this study, we developed an analytical method based on liquid chromatography with electrospray ionization coupled to tandem mass spectrometry detection (LC-ESI-MS/MS). This method was devised to accurately quantify a spectrum of amino acids, notably taurine, creatinine, glutathione (GSH), and sulfur-containing amino acids (SAAs) such as methionine, cysteine, and homocysteine, using only 10 μL of human plasma. A stable isotope derivative of each AA is used as an internal standard (IS) for accurate quantification. For retention and separation on a C18 column, heptafluorobutyric acid (HFBA) was employed as an ion pair agent. Multiple reaction monitoring (MRM) in positive mode with the precursor-to-product ion transitions at m/z is used for quantification. The method showed excellent linearity for all AA with a high correlation coefficient (r > 0.9927). The linear fit indicates that the detector response is linear over the tested range of standard concentrations. The accuracy and precision of the method were within the acceptable range of 92-110% and < 15%, respectively. The limit of detection (LOD) and limit of quantification (LOQ) were in the range of 0.001-1.80 µM and 0.004-6.0 µM, respectively. No significant ion suppression or carry over was observed. In conclusion, the assay was validated and found to have adequate accuracy, precision, linearity, sensitivity and selectivity. The assay has been successfully applied to the analysis of human plasma.

Methyl carbamates of phosphatidylethanolamines and phosphatidylserines reveal bacterial contamination in mitochondrial lipid extracts of mouse embryonic fibroblasts

The occurrence of methyl carbamates of phosphatidylethanolamines and phosphatidylserines in the lipid extract of mitochondria obtained from mouse embryonic fibroblasts was ascertained by hydrophilic interaction liquid chromatography with electrospray ionization single and multi-stage mass spectrometry, performed using sinergically a high resolution (quadrupole-Orbitrap) and a low resolution (linear ion trap) spectrometer. Two possible routes to the synthesis of methyl carbamates of phospholipids were postulated and evaluated: (i) a chemical transformation involving phosgene, occurring as a photooxidation by-product in the chloroform used for lipid extraction, and methanol, also used for the latter; (ii) an enzymatic methoxycarbonylation reaction due to an accidental bacterial contamination, that was unveiled subsequently on the murine mitochondrial sample. A specific lipid extraction performed on a couple of standard phosphatidyl-ethanolamines/-serines, based on purposely photo-oxidized chloroform and deuterated methanol, indicated route (i) as negligible in the specific case, thus highlighting the enzymatic route related to bacterial contamination as the most likely source of methyl carbamates. The unambiguous recognition of the latter might represent the starting point toward a better understanding of their generation in biological systems and a minimization of their occurrence when an artefactual formation is ascertained.

Optimization Strategies for Mass Spectrometry-Based Untargeted Metabolomics Analysis of Small Polar Molecules in Human Plasma

The untargeted approach to mass spectrometry-based metabolomics has a wide potential to investigate health and disease states, identify new biomarkers for diseases, and elucidate metabolic pathways. All this holds great promise for many applications in biological and chemical research. However, the complexity of instrumental parameters on advanced hybrid mass spectrometers can make the optimization of the analytical method immensely challenging. Here, we report a strategy to optimize the selected settings of a hydrophilic interaction liquid chromatography-tandem mass spectrometry method for untargeted metabolomics studies of human plasma, as a sample matrix. Specifically, we evaluated the effects of the reconstitution solvent in the sample preparation procedure, the injection volume employed, and different mass spectrometry-related operating parameters including mass range, the number of data-dependent fragmentation scans, collision energy mode, duration of dynamic exclusion time, and mass resolution settings on the metabolomics data quality and output. This study highlights key instrumental variables influencing the detection of metabolites along with suggested settings for the IQ-X tribrid system and proposes a new methodological framework to ensure increased metabolome coverage.

A multiplatform metabolomics approach for comprehensive analysis of GIST xenografts with various KIT mutations

Metabolites in biological matrices belong to diverse chemical groups, ranging from non-polar long-chain fatty acids to small polar molecules. The goal of untargeted metabolomic analysis is to measure the highest number of metabolites in the sample. Nevertheless, from an analytical point of view, no single technique can measure such a broad spectrum of analytes. Therefore, we selected a method based on GC-MS and LC-MS with two types of stationary phases for the untargeted profiling of gastrointestinal stromal tumours. The procedure was applied to GIST xenograft samples (n = 71) representing four different mutation models, half of which were treated with imatinib. We aimed to verify the method coverage and advantages of applying each technique. RP-LC-MS measured most metabolites due to a significant fraction of lipid components of the tumour tissue. What is unique and worth noting is that all applied techniques were able to distinguish between different mutation models. However, for detecting imatinib-induced alterations in the GIST metabolome, RP-LC-MS and GC-MS proved to be more relevant than HILIC-LC-MS, resulting in a higher number of significantly changed metabolites in four treated models. Undoubtedly, the inclusion of all mentioned techniques makes the method more comprehensive. Nonetheless, for green chemistry and time and labour saving, we assume that RP-LC-MS and GC-MS analyses are sufficient to cover the global GIST metabolome.

Profiling the metabolome of uterine fluid for early detection of ovarian cancer

Ovarian cancer (OC) causes high mortality in women because of ineffective biomarkers for early diagnosis. Here, we perform metabolomics analysis on an initial training set of uterine fluid from 96 gynecological patients. A seven-metabolite-marker panel consisting of vanillylmandelic acid, norepinephrine, phenylalanine, beta-alanine, tyrosine, 12-S-hydroxy-5,8,10-heptadecatrienoic acid, and crithmumdiol is established for detecting early-stage OC. The panel is further validated in an independent sample set from 123 patients, discriminating early OC from controls with an area under the curve (AUC) of 0.957 (95% confidence interval [CI], 0.894-1). Interestingly, we find elevated norepinephrine and decreased vanillylmandelic acid in most OC cells, resulting from excess 4-hydroxyestradiol that antagonizes the catabolism of norepinephrine by catechol-O-methyltransferase. Moreover, exposure to 4-hydroxyestradiol induces cellular DNA damage and genomic instability that could lead to tumorigenesis. Thus, this study not only reveals metabolic features in uterine fluid of gynecological patients but also establishes a noninvasive approach for the early diagnosis of OC.

MetaMOPE: a web service for mobile phase determination and fast chromatography peaks evaluation for metabolomics

Motivation

Liquid chromatography coupled with mass spectrometry (LC-MS) is widely used in metabolomics studies, while HILIC LC-MS is particularly suited for polar metabolites. Determining an optimized mobile phase and developing a proper liquid chromatography method tend to be laborious, time-consuming and empirical.

Results

We developed a containerized web tool providing a workflow to quickly determine the optimized mobile phase by batch-evaluating chromatography peaks for metabolomics LC-MS studies. A mass chromatographic quality value, an asymmetric factor, and the local maximum intensity of the extracted ion chromatogram were calculated to determine the number of peaks and peak retention time. The optimal mobile phase can be quickly determined by selecting the mobile phase that produces the largest number of resolved peaks. Moreover, the workflow enables one to automatically process the repeats by evaluating chromatography peaks and determining the retention time of large standards. This workflow was validated with 20 chemical standards and successfully constructed a reference library of 571 metabolites for the HILIC LC-MS platform.

Availability and implementation

MetaMOPE is freely available at https://metamope.cmdm.tw. Source code and installation instructions are available on GitHub: https://github.com/CMDM-Lab/MetaMOPE.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Performance comparison of narrow-bore and capillary liquid-chromatography for non-targeted metabolomics profiling by HILIC-QTOF-MS

Clinical metabolomics studies often have to cope with limited sample amounts, thus miniaturized liquid chromatography (LC) systems are a promising alternative. Their applicability has already been demonstrated in various fields, including a few metabolomics studies that mainly used reversed-phase chromatography. However, hydrophilic interaction chromatography (HILIC), which is widely used in metabolomics due to its particular suitability for the analysis of polar molecules, has rarely been tested for miniaturized LC-MS analysis of small molecules. In the present work, the suitability of a capillary HILIC (CapHILIC)-QTOF-MS system for non-targeted metabolomics was evaluated based on extracts of porcine formalin-fixed, paraffin-embedded (FFPE) tissue samples. The performance was assessed with respect to the number and retention time span of metabolic features as well as the analytical repeatability, the signal-to-noise ratio and the signal intensity of 16 annotated metabolites from different compound classes. The results were compared with a well established narrow-bore HILIC-QTOF-MS system. Both platforms have detected a similar number of features and performed excellent with respect to retention time stability (median RT span <0.05 min) and analytical repeatability (>75% of features with CV < 20%). The signal areas of all metabolites assessed were increased up to 18-fold by the use of CapHILIC, although the signal-to-noise ratio was only improved for 50% of the metabolites. An even better reproducibility (median CV = 5.2%) and up to 80-fold increase in signal intensity were observed after optimization of CapHILIC conditions for analysis of bile acid standard solutions. Even though the observed improvement for specific bile acids (e.g. taurocholic acid) in biological matrix needs to be evaluated, the platform comparison indicates, that the tested CapHILIC system is particularly suitable for analyses of a less broad metabolite spectrum, and specifically optimized chromatography.

Managing sample introduction problems in hydrophilic interaction liquid chromatography

Sample injection can cause serious problems in hydrophilic interaction liquid chromatography (HILIC) when the injection solvent has higher elution strength than the mobile phase (mp). It can lead to asymmetric peak shapes and poor efficiency. The problem can occur when the mp contains a high proportion of organic e.g. 95% acetonitrile (a weak solvent) whereas the injection solvent contains a higher proportion of water (a strong solvent) that is necessary to dissolve polar samples. We investigated different strategies to overcome this problem. A simple method is pre-column dilution where the injector is programmed to deliver a plug of weak solvent (e.g. pure acetonitrile) along with the sample dissolved in a solvent with higher water content than the mp. Another option is to use alternative organic solvents to acetonitrile in the injection solvent, e.g. isopropanol, acetone or tetrahydrofuran, that may give enhanced sample solubility. The role of the volume of injection solvents was investigated as well as the possible effects of mass overload on the results. The use of small sample volumes is always recommended to reduce mismatch effects.

Feature-Based Molecular Networking Facilitates the Comprehensive Identification of Differential Metabolites in Diabetic Cognitive Dysfunction Rats

Cognitive dysfunction is a frequent complication of type 2 diabetes mellitus (T2DM), usually accompanied by metabolic disorders. However, the metabolic changes in diabetic cognitive dysfunction (DCD) patients, especially compared to T2DM groups, are not fully understood. Due to the subtle differences in metabolic alterations between DCD groups and T2DM groups, the comprehensive detection of the untargeted metabolic profiles of hippocampus and urine samples of rats was conducted by LC-MS, considering the different ionization modes and polarities of the examined compounds, and feature-based molecular networking (FBMN) was performed to help identify differential metabolites from a comprehensive perspective in this study. In addition, an association analysis of the differential metabolites in hippocampus and urine was conducted by the O2PLS model. Finally, a total of 71 hippocampal tissue differential metabolites and 179 urine differential metabolites were identified. The pathway enrichment results showed that glutamine and glutamate metabolism, alanine, aspartate, and glutamate metabolism, glycerol phospholipid metabolism, TCA cycle, and arginine biosynthesis in the hippocampus of DCD animals were changed. Seven metabolites (AUC > 0.9) in urine appeared as key differential metabolites that might reflect metabolic changes in the target tissue of DCD rats. This study showed that FBMN facilitated the comprehensive identification of differential metabolites in DCD rats. The differential metabolites may suggest an underlying DCD and be considered as potential biomarkers for DCD. Large samples and clinical experiments are needed for the subsequent elucidation of the possible mechanisms leading to these alterations and the verification of potential biomarkers.

Status of Metabolomic Measurement for Insights in Alzheimer's Disease Progression-What Is Missing?

Alzheimer's disease (AD) is an aging-related neurodegenerative disease, leading to the progressive loss of memory and other cognitive functions. As there is still no cure for AD, the growth in the number of susceptible individuals represents a major emerging threat to public health. Currently, the pathogenesis and etiology of AD remain poorly understood, while no efficient treatments are available to slow down the degenerative effects of AD. Metabolomics allows the study of biochemical alterations in pathological processes which may be involved in AD progression and to discover new therapeutic targets. In this review, we summarized and analyzed the results from studies on metabolomics analysis performed in biological samples of AD subjects and AD animal models. Then this information was analyzed by using MetaboAnalyst to find the disturbed pathways among different sample types in human and animal models at different disease stages. We discuss the underlying biochemical mechanisms involved, and the extent to which they could impact the specific hallmarks of AD. Then we identify gaps and challenges and provide recommendations for future metabolomics approaches to better understand AD pathogenesis.

Miniaturized Two-Dimensional Heart Cutting for LC-MS-Based Metabolomics

Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics usually combines hydrophilic interaction liquid chromatography (HILIC) and reversed-phase (RP) chromatography to cover a wide range of metabolomes, requiring both significant sample consumption and analysis time for separate workflows. We developed an integrated workflow enabling the coverage of both polar and nonpolar metabolites with only one injection of the sample for each ionization mode using heart-cutting trapping to combine HILIC and RP separations. This approach enables the trapping of some compounds eluted from the first chromatographic dimension for separation later in the second dimension. In our case, we applied heart-cutting to non-retained metabolites in the first dimension. For that purpose, two independent miniaturized one-dimensional HILIC and RP methods were developed by optimizing the chromatographic and ionization conditions using columns with an inner diameter of 1 mm. They were then merged into one two-dimensional micro LC-MS method by optimization of the trapping conditions. Equilibration of the HILIC column during elution on the RP column and vice versa reduced the overall analysis time, and the multidimensionality allows us to avoid signal measurements during the solvent front. To demonstrate the benefits of this approach to metabolomics, it was applied to the analysis of the human plasma standard reference material SRM 1950, enabling the detection of hundreds of metabolites without the significant loss of some of them while requiring an injection volume of only 0.5 μL.

The effect of root hairs on exudate composition: a comparative non-targeted metabolomics approach

Root exudation is a major pathway of organic carbon input into soils. It affects soil physical properties, element solubility as well as speciation, and impacts the microbial community in the rhizosphere. Root exudates contain a large number of primary and secondary plant metabolites, and the amount and composition are highly variable depending on plant species and developmental stage. Detailed information about exudate composition will allow for a better understanding of exudate-driven rhizosphere processes and their feedback loops. Although non-targeted metabolomics by high-resolution mass spectrometry is an established tool to characterize root exudate composition, the extent and depth of the information obtained depends strongly on the analytical approach applied. Here, two genotypes of Zea mays L., differing in root hair development, were used to compare six mass spectrometric approaches for the analysis of root exudates. Reversed-phase liquid chromatography and hydrophilic interaction liquid chromatography combined with time-of-flight mass spectrometry (LC-TOF-MS), as well as direct infusion Fourier-transform ion cyclotron resonance mass spectrometry (DI-FT-ICR-MS), were applied with positive and negative ionization mode. By using the same statistical workflow, the six approaches resulted in different numbers of detected molecular features, ranging from 176 to 889, with a fraction of 48 to 69% of significant features (fold change between the two genotypes of > 2 and p-value < 0.05). All approaches revealed the same trend between genotypes, namely up-regulation of most metabolites in the root hair defective mutant (rth3). These results were in agreement with the higher total carbon and nitrogen exudation rate of the rth3-mutant as compared to the corresponding wild-type maize (WT). However, only a small fraction of features were commonly found across the different analytical approaches (20-79 features, 13-31% of the rth3-mutant up-regulated molecular formulas), highlighting the need for different mass spectrometric approaches to obtain a more comprehensive view into the composition of root exudates. In summary, 111 rth3-mutant up-regulated compounds (92 different molecular formulas) were detected with at least two different analytical approaches, while no WT up-regulated compound was found by both, LC-TOF-MS and DI-FT-ICR-MS. Zea mays L. exudate features obtained with multiple analytical approaches in our study were matched against the metabolome database of Zea mays L. (KEGG) and revealed 49 putative metabolites based on their molecular formula.

Optimization of Mobile Phase Modifiers for Fast LC-MS-Based Untargeted Metabolomics and Lipidomics

Liquid chromatography-mass spectrometry (LC-MS) is the method of choice for the untargeted profiling of biological samples. A multiplatform LC-MS-based approach is needed to screen polar metabolites and lipids comprehensively. Different mobile phase modifiers were tested to improve the electrospray ionization process during metabolomic and lipidomic profiling. For polar metabolites, hydrophilic interaction LC using a mobile phase with 10 mM ammonium formate/0.125% formic acid provided the best performance for amino acids, biogenic amines, sugars, nucleotides, acylcarnitines, and sugar phosphate, while reversed-phase LC (RPLC) with 0.1% formic acid outperformed for organic acids. For lipids, RPLC using a mobile phase with 10 mM ammonium formate or 10 mM ammonium formate with 0.1% formic acid permitted the high signal intensity of various lipid classes ionized in ESI(+) and robust retention times. For ESI(-), the mobile phase with 10 mM ammonium acetate with 0.1% acetic acid represented a reasonable compromise regarding the signal intensity of the detected lipids and the stability of retention times compared to 10 mM ammonium acetate alone or 0.02% acetic acid. Collectively, we show that untargeted methods should be evaluated not only on the total number of features but also based on common metabolites detected by a specific platform along with the long-term stability of retention times.

Metabolomics in hepatocellular carcinoma: From biomarker discovery to precision medicine

Hepatocellular carcinoma (HCC) remains a global health burden, and is mostly diagnosed at late and advanced stages. Currently, limited and insensitive diagnostic modalities continue to be the bottleneck of effective and tailored therapy for HCC patients. Moreover, the complex reprogramming of metabolic patterns during HCC initiation and progression has been obstructing the precision medicine in clinical practice. As a noninvasive and global screening approach, metabolomics serves as a powerful tool to dynamically monitor metabolic patterns and identify promising metabolite biomarkers, therefore holds a great potential for the development of tailored therapy for HCC patients. In this review, we summarize the recent advances in HCC metabolomics studies, including metabolic alterations associated with HCC progression, as well as novel metabolite biomarkers for HCC diagnosis, monitor, and prognostic evaluation. Moreover, we highlight the application of multi-omics strategies containing metabolomics in biomarker discovery for HCC. Notably, we also discuss the opportunities and challenges of metabolomics in nowadays HCC precision medicine. As technologies improving and metabolite biomarkers discovering, metabolomics has made a major step toward more timely and effective precision medicine for HCC patients.

Metabolomics: Going Deeper, Going Broader, Going Further

Metabolomics is a continuously dynamic field of research that is driven by demanding research questions and technological advances alike. In this review we highlight selected recent and ongoing developments in the area of mass spectrometry-based metabolomics. The field of view that can be seen through the metabolomics lens can be broadened by adoption of separation techniques such as hydrophilic interaction chromatography and ion mobility mass spectrometry (going broader). For a given biospecimen, deeper metabolomic analysis can be achieved by resolving smaller entities such as rare cell populations or even single cells using nano-LC and spatially resolved metabolomics or by extracting more useful information through improved metabolite identification in untargeted metabolomic experiments (going deeper). Integration of metabolomics with other (omics) data allows researchers to further advance in the understanding of the complex metabolic and regulatory networks in cells and model organisms (going further). Taken together, diverse fields of research from mechanistic studies to clinics to biotechnology applications profit from these technological developments.

Evaluation and optimization of analytical procedure and sample preparation for polar Streptomyces albus J1074 metabolome profiling

Metabolomics is an essential discipline in omics technology that promotes research on the biology of microbial systems. Streptomyces albus J1074 is a model organism used in fundamental research and industrial microbiology. Nevertheless, a comprehensive and standardized method for analyzing the metabolome of S. albus J1074 is yet to be developed. Thus, we comprehensively evaluated and optimized the analytical procedure and sample preparation for profiling polar metabolites using hydrophilic interaction liquid chromatography (HILIC) coupled with high-resolution mass spectrometry (HRMS). We systematically examined the HILIC columns, quenching solutions, sample-to-quenching ratios, and extraction methods. Then, the optimal protocol was used to investigate the dynamic intracellular polar metabolite profile of the engineered S. albus J1074 strains during spinosad (spinosyn A and spinosyn D) fermentation. A total of 3648 compounds were detected, and 83 metabolites were matched to the standards. The intracellular metabolomic profiles of engineered S. albus J1074 strains (ADE-AP and OE3) were detected; furthermore, their metabolomes in different stages were analyzed to reveal the reasons for their differences in their spinosad production, as well as the current metabolic limitation of heterologous spinosad production in S. albus J1074. The HILIC-HRMS method is a valuable tool for investigating polar metabolomes, and provides a reference methodology to study other Streptomyces metabolomes.

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A HILIC-HRMS method was developed for polar metabolome profiling.

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Sample preparation protocol for Streptomyces albus J1074 intracellular metabolites was studied for the first time.

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This study revealed the possible reasons for different production of spinosad of engineered S. albus J1074 strains.

Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics

Researchers worldwide are taking advantage of novel, commercially available, technologies, such as ion mobility mass spectrometry (IM-MS), for metabolomics and lipidomics applications in a variety of fields including life, biomedical, and food sciences. IM-MS provides three main technical advantages over traditional LC-MS workflows. Firstly, in addition to mass, IM-MS allows collision cross-section values to be measured for metabolites and lipids, a physicochemical identifier related to the chemical shape of an analyte that increases the confidence of identification. Second, IM-MS increases peak capacity and the signal-to-noise, improving fingerprinting as well as quantification, and better defining the spatial localization of metabolites and lipids in biological and food samples. Third, IM-MS can be coupled with various fragmentation modes, adding new tools to improve structural characterization and molecular annotation. Here, we review the state-of-the-art in IM-MS technologies and approaches utilized to support metabolomics and lipidomics applications and we assess the challenges and opportunities in this growing field.

Integration of solid phase extraction with HILIC-MS/MS for analysis of free amino acids in source water

Amino acids (AAs) are prevalent in source water, particularly during spring run-off. Monitoring of amino acids in source water is desirable for water treatment plants (WTP) to indicate changes in source water quality. The objective of this study was to establish analytical procedures for reliable monitoring of amino acids in source water. Therefore, we examined two different methods, large volume inject (LVI) and solid phase extraction (SPE), for sample preparation prior to HILIC-MS/MS. The LVI-HILIC-MS/MS method can provide fast and sensitive detection for clean samples, but suffers from matrix effects, resulting in irreproducible separation and shortening column lifetime. We have demonstrated that SPE was necessary prior to HILIC-MS/MS to achieve reproducible and reliable quantification of AAs in source water. A natural heterocyclic amine 1-methyl-1,2,3,4-tetrahydro-β-carboline-3-carboxylic acid (MTCCA) was also included in the method to indicate changes in other natural nitrogenous compounds in source water. The SPE-HILIC-MS/MS method was able to achieve limits of detection from 2.6-3400 ng/L for the amino acids and MTCCA with RSDs (n=3) of 1.1%-4.8%. As well, retention times (RT) of the analytes were reproducible with variation less than 0.01 min (n=3) through the entire project. We further applied the SPE-HILIC-MS/MS method to determine AAs in authentic source water samples collected from two drinking water treatment plants (WTPs) during the 2021 spring run-off season. The results support that the SPE-HILIC-MS/MS method does not require derivatization and can provide reliable, accurate, and robust analysis of AAs and MTCCA in source water, supporting future monitoring of source water quality.

Quantitative analysis of 20 purine and pyrimidine metabolites by HILIC-MS/MS in the serum and hippocampus of depressed mice

Purine and pyrimidine metabolism are vital metabolic pathways in the development, proliferation or repairment of cells or tissues associated with various diseases. Here, a simple, all-in-one injection hydrophilic interaction liquid chromatography-tandem mass spectrometry method was developed for simultaneous determination of 20 metabolites: adenine, adenosine, deoxyadenosine, adenosine 5'-monophosphate, cyclic adenosine monophosphate, hypoxanthine, xanthine, inosine, deoxyinosine, xanthosine, xanthosine 5'-monophosphate and uric acid, which are products of purine metabolism; uridine, deoxyuridine, uridine 5'-monophosphate and uracil, are products of pyrimidine metabolism; and corticosterone, methionine, acetylcholine and serotonin. To minimize interference of endogenous molecules in sample matrixes, a combination of activated carbon adsorption and a serum substitute matrix (5% bovine serum albumin in phosphate buffered saline) was utilized and jointly applied. The sensitivity, linearity, stability, precision, accuracy and extraction recovery were evaluated, and the method was demonstrated to be accurate, sensitive and reliable. An analytical strategy was successfully applied to quantitatively determine 20 metabolite levels in the serum and hippocampus of mice with chronic social defeat stress-induced depression. The results showed greatly perturbed purine metabolism in the depressed mice, which was primarily characterized by dramatic increases in hypoxanthine, xanthine and inosine in serum and reduced levels of adenine, adenosine and adenosine 5'-monophosphate in the hippocampus. These findings suggest that this novel strategy can facilitate the quantitative analysis of adenine and other purine and pyrimidine metabolites in tissue and serum and exhibits great potential in the exploration of metabolism-related mechanisms of relevant diseases.

Mechanistic insights into the key marine dimethylsulfoniopropionate synthesis enzyme DsyB/DSYB

Marine algae and bacteria produce approximately eight billion tonnes of the organosulfur molecule dimethylsulfoniopropionate (DMSP) in Earth's surface oceans annually. DMSP is an antistress compound and, once released into the environment, a major nutrient, signaling molecule, and source of climate-active gases. The methionine transamination pathway for DMSP synthesis is used by most known DMSP-producing algae and bacteria. The S-directed S-adenosylmethionine (SAM)-dependent 4-methylthio-2-hydroxybutyrate (MTHB) S-methyltransferase, encoded by the dsyB/DSYB gene, is the key enzyme of this pathway, generating S-adenosylhomocysteine (SAH) and 4-dimethylsulfonio-2-hydroxybutyrate (DMSHB). DsyB/DSYB, present in most haptophyte and dinoflagellate algae with the highest known intracellular DMSP concentrations, is shown to be far more abundant and transcribed in marine environments than any other known S-methyltransferase gene in DMSP synthesis pathways. Furthermore, we demonstrate in vitro activity of the bacterial DsyB enzyme from Nisaea denitrificans and provide its crystal structure in complex with SAM and SAH-MTHB, which together provide the first important mechanistic insights into a DMSP synthesis enzyme. Structural and mutational analyses imply that DsyB adopts a proximity and desolvation mechanism for the methyl transfer reaction. Sequence analysis suggests that this mechanism may be common to all bacterial DsyB enzymes and also, importantly, eukaryotic DSYB enzymes from e.g., algae that are the major DMSP producers in Earth's surface oceans.

Ion-Pairing Chromatography and Amine Derivatization Provide Complementary Approaches for the Targeted LC-MS Analysis of the Polar Metabolome

Liquid chromatography coupled to mass spectrometry is a key metabolomics/metabonomics technology. Reversed-phase liquid chromatography (RPLC) is very widely used as a separation step, but typically has poor retention of highly polar metabolites. Here, we evaluated the combination of two alternative methods for improving retention of polar metabolites based on 6-aminoquinoloyl-N-hydroxysuccinidimyl carbamate derivatization for amine groups, and ion-pairing chromatography (IPC) using tributylamine as an ion-pairing agent to retain acids. We compared both of these methods to RPLC and also to each other, for targeted analysis using a triple-quadrupole mass spectrometer, applied to a library of ca. 500 polar metabolites. IPC and derivatization were complementary in terms of their coverage: combined, they improved the proportion of metabolites with good retention to 91%, compared to just 39% for RPLC alone. The combined method was assessed by analyzing a set of liver extracts from aged male and female mice that had been treated with the polyphenol compound ampelopsin. Not only were a number of significantly changed metabolites detected, but also it could be shown that there was a clear interaction between ampelopsin treatment and sex, in that the direction of metabolite change was opposite for males and females.

automRm: An R Package for Fully Automatic LC-QQQ-MS Data Preprocessing Powered by Machine Learning

Preprocessing of liquid chromatography-mass spectrometry (LC-MS) raw data facilitates downstream statistical and biological data analyses. In the case of targeted LC-MS data, consistent recognition of chromatographic peaks is a main challenge, in particular, for low abundant signals. Fully automatic preprocessing is faster than manual peak review and does not depend on the individual operator. Here, we present the R package automRm for fully automatic preprocessing of LC-MS data recorded in MRM mode. Using machine learning (ML) for detection of chromatographic peaks and quality control of reported results enables the automatic recognition of complex patterns in raw data. In addition, this approach renders automRm generally applicable to a wide range of analytical methods including hydrophilic interaction liquid chromatography (HILIC), which is known for sample-to-sample variations in peak shape and retention time. We demonstrate the impact of the choice of training data set, of the applied ML algorithm, and of individual peak characteristics on automRm's ability to correctly report chromatographic peaks. Next, we show that automRm can replicate results obtained by manual peak review on published data. Moreover, automRm outperforms alternative software solutions regarding the variation in peak integration among replicate measurements and the number of correctly reported peaks when applied to a HILIC-MS data set. The R package is freely available from gitlab (https://gitlab.gwdg.de/joerg.buescher/automrm).